├── CHANGELOG.md ├── LICENSE ├── README.md ├── arxivsearch ├── __init__.py ├── topic.py └── utils.py ├── bin ├── concatenate ├── search └── update_all ├── bnn └── README.md ├── causal └── README.md ├── fairness └── README.md ├── interpretable └── README.md ├── mcmc ├── README.md ├── new_df.csv └── readme_df.csv └── variational └── README.md /CHANGELOG.md: -------------------------------------------------------------------------------- 1 | # 05/12/2018 2 | Changed naming convention to be more consistent with arXiv API (commit dd0f18b59459922bad853ec8fe05c678ec3f2ac0) 3 | The arXiv API defines what a category is, such as `stat.ML`, `cs.CV` etc. In my code I called a category something different, so I updated my code to be consistent with that. 4 | 5 | - changed `category` to `topic` 6 | - changed `subject` to `category` 7 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2018 Ethan Goan 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # arxivsearch 2 | 3 | Repo that automatically pulls links to new eprints published on arXiv 4 | for machine learning research related to Bayesian methods for machine learning. 5 | Papers are found for key search terms listed against specific catagories. 6 | Current catagories are, bnn, causal, interpretable and variational. 7 | Papers are displayed in a markdown format, inspired by 8 | [arXausality by Logan Graham](https://github.com/logangraham/arxausality), 9 | who displays new papers relating to causality and machine learning. 10 | This project works in a similar (though less comprehensive in implelementation), 11 | but allows for additional search catagories to be included. The papers for 12 | each catagory are listed in each corresponding directory. 13 | 14 | Currently Supported Search Catagories: 15 | 16 | [BNNs (Bayesian Neural Netyworks)](https://github.com/ethangoan/arxivsearch/tree/master/bnn) 17 | 18 | [Causal Inference (Link to arXausality by Logan Graham)](https://github.com/logangraham/arxausality) 19 | 20 | [Fairness in Statistics and Machine Learning](https://github.com/ethangoan/arxivsearch/tree/master/fairness) 21 | 22 | [Interpretable Machine Learning](https://github.com/ethangoan/arxivsearch/tree/master/interpretable) 23 | 24 | [Variational (and other approximation) Methods](https://github.com/ethangoan/arxivsearch/tree/master/variational) 25 | 26 | [MCMC (and other sampling based methods)](https://github.com/ethangoan/arxivsearch/tree/master/mcmc) 27 | 28 | This Repo is automatically updated once a week on Fridays 12:30pm AEST (+10 GMT) 29 | 30 | If you have used a previous commit of this package for your own searches and wish to update, have a look at the [CHANGELOG.md](./CHANGELOG.md) which describes any changes (mostly formatting and name changes to become consistent with the arXiv API). 31 | 32 | ## Install 33 | ```bash 34 | #install arxivpy 35 | pip install git+https://github.com/titipata/arxivpy 36 | #clone this repo 37 | git clone https://github.com/ethangoan/arxivsearch.git 38 | #add this module to your PYTHONPATH 39 | export PYTHONPATH=$PYTHONPATH:// 40 | ``` 41 | To add this package to your Python path permanently (on Linux), you can run the commands 42 | ```bash 43 | echo export PYTHONPATH=\$PYTHONPATH:// >> ~/.bashrc 44 | source ~/.bashrc 45 | ``` 46 | 47 | ## Running 48 | Searching for recent preprints: 49 | ```bash 50 | # search most recent papers from specified field 51 | # should be in format of: 52 | # ./bin/search 53 | ./bin/search variational 54 | ``` 55 | Concatenating the search reseults from the `search` script with previous search results and displaying them in a markdown format: 56 | ```bash 57 | # ./bin/concatenate 58 | ./bin/concatenate variational 59 | ``` 60 | To update all categories, cocnatenate the results and push to Github: 61 | ```bash 62 | ./bin/update_all 63 | ``` 64 | 65 | I have made a bash script that will change to the directory of this repo, 66 | and then run the update script to push everything to this repo. This script 67 | is then added to cron so that it can be set to automatically run once a week. 68 | 69 | ## Adding Your own Terms 70 | To add your own search catagory, 71 | 1. add a your own category class in `category.py` that inherits from the `category` class 72 | 2. set your general and specific terms as done in the other classes (look for some notes below on how you might want to specify these) 73 | 3. Add your class selection to the `get_category()` method 74 | 4. Update the `InvalidCategoryError` exception string at the top to an informative error message of your choice 75 | 5. You can stop here if you just want to run the `search` script, but if you want to run the concatenate and update all script keep playing along 76 | 6. Update the `bin/update_all` script to include the new search classes you made 77 | 7. If you want to use the Git markdown functionality, you will have to store your credentials using `git config credential.helper store`. You will also have to change the remote path to your own repo where you can push to. 78 | 8. On a Linux machine, you can add the running the `update_all` script to `cron` to schedule it to run automatically (Will be able to do something similar on Windows or Mac) 79 | 80 | ## How the search will work 81 | The search function has 3 fields, the `subject`, `generic_terms` and `specific_terms`. 82 | The `subject` refers to the arXiv subject category where the preprint was submitted. These are listed at the bottom of this page. You can specify which subject/category you want to search for in the `self.subject` attribute in the `category` parent class. The search function will only search within these categories. 83 | 84 | The next terms are the `general_terms` and the `specific_terms`. The `general_terms` should be broad terms that are related to your field, for example, for my `fairness` category, I include general terms such as `equality` and `bias` which are common terms used when discussing fairness in systems. The `specific_terms` should be specific to your field of interest. Again, for the `fairness` category, I use specific terms such as `algorithms` and `statistics` to limit my search results to fairness preprints within the context of statistics and machine learning. 85 | 86 | The search will work in the format of, 87 | 88 | `within_category & general_terms & specific_terms` 89 | 90 | where it will iterate over all of the different combinations of your terms. 91 | 92 | ### Formatting terms 93 | The [arXiv API](https://arxiv.org/help/api/user-manual) describes a funky way for formatting your search queries. If you have multiple words in a term you want to search for, you need to format it in a way that arXiv will handle properly. For example, say you want to search for the term `Monte Carlo`, you will need to set your search term to `%22Monte+Carlo%22`. The `%22` is basically a code that translates into double quotes, and the `+` sign is there as the URL that is sent to arXiv for the query can't handle spaces. I might automate this formatting at some point so you don't need to do this. 94 | 95 | ## Contact 96 | If you have any questions, or want me to add a catagory, please feel free to email me 97 | 98 | Ethan Goan 99 | ethanjgoan@gmail.com 100 | 101 | 102 | ## arXiv Subject Categories 103 | ``` 104 | astro-ph Astrophysics 105 | astro-ph.CO Cosmology and Nongalactic Astrophysics 106 | astro-ph.EP Earth and Planetary Astrophysics 107 | astro-ph.GA Astrophysics of Galaxies 108 | astro-ph.HE High Energy Astrophysical Phenomena 109 | astro-ph.IM Instrumentation and Methods for Astrophysics 110 | astro-ph.SR Solar and Stellar Astrophysics 111 | cond-mat.dis-nn Disordered Systems and Neural Networks 112 | cond-mat.mes-hall Mesoscale and Nanoscale Physics 113 | cond-mat.mtrl-sci Materials Science 114 | cond-mat.other Other Condensed Matter 115 | cond-mat.quant-gas Quantum Gases 116 | cond-mat.soft Soft Condensed Matter 117 | cond-mat.stat-mech Statistical Mechanics 118 | cond-mat.str-el Strongly Correlated Electrons 119 | cond-mat.supr-con Superconductivity 120 | cs.AI Artificial Intelligence 121 | cs.AR Hardware Architecture 122 | cs.CC Computational Complexity 123 | cs.CE Computational Engineering, Finance, and Science 124 | cs.CG Computational Geometry 125 | cs.CL Computation and Language 126 | cs.CR Cryptography and Security 127 | cs.CV Computer Vision and Pattern Recognition 128 | cs.CY Computers and Society 129 | cs.DB Databases 130 | cs.DC Distributed, Parallel, and Cluster Computing 131 | cs.DL Digital Libraries 132 | cs.DM Discrete Mathematics 133 | cs.DS Data Structures and Algorithms 134 | cs.ET Emerging Technologies 135 | cs.FL Formal Languages and Automata Theory 136 | cs.GL General Literature 137 | cs.GR Graphics 138 | cs.GT Computer Science and Game Theory 139 | cs.HC Human-Computer Interaction 140 | cs.IR Information Retrieval 141 | cs.IT Information Theory 142 | cs.LG Machine Learning 143 | cs.LO Logic in Computer Science 144 | cs.MA Multiagent Systems 145 | cs.MM Multimedia 146 | cs.MS Mathematical Software 147 | cs.NA Numerical Analysis 148 | cs.NE Neural and Evolutionary Computing 149 | cs.NI Networking and Internet Architecture 150 | cs.OH Other Computer Science 151 | cs.OS Operating Systems 152 | cs.PF Performance 153 | cs.PL Programming Languages 154 | cs.RO Robotics 155 | cs.SC Symbolic Computation 156 | cs.SD Sound 157 | cs.SE Software Engineering 158 | cs.SI Social and Information Networks 159 | cs.SY Systems and Control 160 | econ.EM Econometrics 161 | eess.AS Audio and Speech Processing 162 | eess.IV Image and Video Processing 163 | eess.SP Signal Processing 164 | gr-qc General Relativity and Quantum Cosmology 165 | hep-ex High Energy Physics - Experiment 166 | hep-lat High Energy Physics - Lattice 167 | hep-ph High Energy Physics - Phenomenology 168 | hep-th High Energy Physics - Theory 169 | math.AC Commutative Algebra 170 | math.AG Algebraic Geometry 171 | math.AP Analysis of PDEs 172 | math.AT Algebraic Topology 173 | math.CA Classical Analysis and ODEs 174 | math.CO Combinatorics 175 | math.CT Category Theory 176 | math.CV Complex Variables 177 | math.DG Differential Geometry 178 | math.DS Dynamical Systems 179 | math.FA Functional Analysis 180 | math.GM General Mathematics 181 | math.GN General Topology 182 | math.GR Group Theory 183 | math.GT Geometric Topology 184 | math.HO History and Overview 185 | math.IT Information Theory 186 | math.KT K-Theory and Homology 187 | math.LO Logic 188 | math.MG Metric Geometry 189 | math.MP Mathematical Physics 190 | math.NA Numerical Analysis 191 | math.NT Number Theory 192 | math.OA Operator Algebras 193 | math.OC Optimization and Control 194 | math.PR Probability 195 | math.QA Quantum Algebra 196 | math.RA Rings and Algebras 197 | math.RT Representation Theory 198 | math.SG Symplectic Geometry 199 | math.SP Spectral Theory 200 | math.ST Statistics Theory 201 | math-ph Mathematical Physics 202 | nlin.AO Adaptation and Self-Organizing Systems 203 | nlin.CD Chaotic Dynamics 204 | nlin.CG Cellular Automata and Lattice Gases 205 | nlin.PS Pattern Formation and Solitons 206 | nlin.SI Exactly Solvable and Integrable Systems 207 | nucl-ex Nuclear Experiment 208 | nucl-th Nuclear Theory 209 | physics.acc-ph Accelerator Physics 210 | physics.ao-ph Atmospheric and Oceanic Physics 211 | physics.app-ph Applied Physics 212 | physics.atm-clus Atomic and Molecular Clusters 213 | physics.atom-ph Atomic Physics 214 | physics.bio-ph Biological Physics 215 | physics.chem-ph Chemical Physics 216 | physics.class-ph Classical Physics 217 | physics.comp-ph Computational Physics 218 | physics.data-an Data Analysis, Statistics and Probability 219 | physics.ed-ph Physics Education 220 | physics.flu-dyn Fluid Dynamics 221 | physics.gen-ph General Physics 222 | physics.geo-ph Geophysics 223 | physics.hist-ph History and Philosophy of Physics 224 | physics.ins-det Instrumentation and Detectors 225 | physics.med-ph Medical Physics 226 | physics.optics Optics 227 | physics.plasm-ph Plasma Physics 228 | physics.pop-ph Popular Physics 229 | physics.soc-ph Physics and Society 230 | physics.space-ph Space Physics 231 | q-bio.BM Biomolecules 232 | q-bio.CB Cell Behavior 233 | q-bio.GN Genomics 234 | q-bio.MN Molecular Networks 235 | q-bio.NC Neurons and Cognition 236 | q-bio.OT Other Quantitative Biology 237 | q-bio.PE Populations and Evolution 238 | q-bio.QM Quantitative Methods 239 | q-bio.SC Subcellular Processes 240 | q-bio.TO Tissues and Organs 241 | q-fin.CP Computational Finance 242 | q-fin.EC Economics 243 | q-fin.GN General Finance 244 | q-fin.MF Mathematical Finance 245 | q-fin.PM Portfolio Management 246 | q-fin.PR Pricing of Securities 247 | q-fin.RM Risk Management 248 | q-fin.ST Statistical Finance 249 | q-fin.TR Trading and Market Microstructure 250 | quant-ph Quantum Physics 251 | stat.AP Applications 252 | stat.CO Computation 253 | stat.ME Methodology 254 | stat.ML Machine Learning 255 | stat.OT Other Statistics 256 | stat.TH Statistics Theory 257 | ``` 258 | 259 | ### TODO 260 | 261 | - [X] Change the way I combine searches from previous week (save a dataframe instead of a markdown file) 262 | 263 | - [ ] Add automated formatting 264 | -------------------------------------------------------------------------------- /arxivsearch/__init__.py: -------------------------------------------------------------------------------- 1 | from arxivsearch import * 2 | -------------------------------------------------------------------------------- /arxivsearch/topic.py: -------------------------------------------------------------------------------- 1 | import abc 2 | import six 3 | 4 | #setting up some exceptions 5 | class InvalidTopic(TypeError): 6 | def __init__(self, arg): 7 | print("""Incorrect type for initialising topic. 8 | Input {} of type {} """.format(arg, type(arg))) 9 | print(""" Expecting either "bnn","interpretable", "fairness", "mcmc" or "variational" """) 10 | 11 | 12 | 13 | @six.add_metaclass(abc.ABCMeta) 14 | class topic(object): 15 | """Abstract Class for search topics 16 | 17 | Class defines methods for formatting search terms. 18 | Any topic that you want to search for should inherit from this class, 19 | and define the exact general and specific terms you want to search for. 20 | """ 21 | def __init__(self, dirname, category=None): 22 | """Initialises variables and path 23 | 24 | Args: 25 | dirname (str): 26 | name of the directory where the results will be stored 27 | Will also be the name of the topic you a sreaching for 28 | category (default=None): 29 | The arXiv categories you want to search under, 30 | Eg. cs.CV, stat.ML etc. If nothing is specified, will use the 31 | parameters specified in this init method. 32 | """ 33 | self.dirname = dirname 34 | if category == None: 35 | self.category = ['cs.CV', 'cs.LG', 'cs.CL', 'cs.NE', 'stat.ML'] 36 | else: 37 | self.category = category 38 | self.general_terms = [] 39 | self.specific_terms = [] 40 | 41 | 42 | def format_search(self): 43 | """ 44 | format_search() 45 | Description: 46 | Will create the complete list of different combination 47 | of search terms for you. 48 | 49 | Keyword Arguments: 50 | 51 | Returns: 52 | (list(string)) of all different search combinations 53 | """ 54 | search = [] 55 | for sub in self.category: 56 | for gen in self.general_terms: 57 | search_string = 'cat:{}+AND+%28ti:{}+OR+abs:{}%29+AND+%28'.format( 58 | sub, gen, gen) 59 | 60 | #remove the last +OR+ from the string 61 | for spec in self.specific_terms: 62 | search_string += 'all:' + spec + '+OR+' 63 | #remove the last +OR+ from the string 64 | search_string = search_string[:-4] + '%29' 65 | #add the suffix to say how to order the list 66 | search_string += '&sortBy=submittedDate&sortOrder=descending' 67 | #now add this search string to the list 68 | search.append(search_string) 69 | return search 70 | 71 | 72 | class bnn_topic(topic): 73 | def __init__(self): 74 | topic.__init__(self, 'bnn') 75 | self.general_terms = [ 76 | 'bayesian', 77 | 'probabilistic' 78 | ] 79 | self.specific_terms = [ 80 | 'convol', 81 | 'neural', 82 | 'uncertain', 83 | 'variational', 84 | 'inference', 85 | 'marginali' 86 | ] 87 | 88 | 89 | class fairness_topic(topic): 90 | def __init__(self): 91 | topic.__init__(self, 'fairness') 92 | self.general_terms = [ 93 | 'fairness', 94 | 'bias', 95 | 'ethic', 96 | 'equality', 97 | 'equal' 98 | ] 99 | self.specific_terms = [ 100 | 'algorithms', 101 | 'accountability', 102 | 'transparency', 103 | 'discrimination', 104 | 'legal', 105 | 'social', 106 | 'unfair', 107 | 'audit', 108 | '%22machine+learning%22', 109 | '%22artificial+intelligence%22', 110 | 'statistics' 111 | ] 112 | 113 | 114 | class interpretable_topic(topic): 115 | def __init__(self): 116 | topic.__init__(self, 'interpretable') 117 | self.general_terms = [ 118 | 'interpretab', 119 | 'explain', 120 | 'understandab', 121 | 'artificial' 122 | 'machine' 123 | 'learning' 124 | ] 125 | self.specific_terms = [ 126 | 'reason', 127 | 'cause', 128 | 'trust' 129 | ] 130 | 131 | 132 | 133 | class variational_topic(topic): 134 | #also include Monte Carlo methods 135 | def __init__(self): 136 | topic.__init__(self, 'variational') 137 | self.general_terms = [ 138 | '%22variational+inference%22', 139 | 'approximat', 140 | 'bayesian', 141 | 'probabilistic', 142 | 'uncertain' 143 | ] 144 | self.specific_terms = [ 145 | 'ELBO', 146 | 'divergence' 147 | 'marginali', 148 | 'uncertain', 149 | 'stochastic', 150 | 'reparameterization' 151 | ] 152 | 153 | 154 | class mcmc_topic(topic): 155 | def __init__(self): 156 | topic.__init__(self, 'bnn') 157 | self.general_terms = [ 158 | 'bayesian', 159 | 'probabilistic' 160 | ] 161 | self.specific_terms = [ 162 | '%22Monte+Carlo%22', 163 | 'MCMC', 164 | '%22Metropolis+Hastings%22', 165 | 'HMC', 166 | '%22Hybrid+Monte+Carlo%22', 167 | '%22Hamiltonian+Monte+Carlo%22', 168 | 'PDMP', 169 | '%22Piecewise+Deterministic+Markov+Process%22', 170 | '%22Piecewise-Deterministic+Markov+Process%22' 171 | ] 172 | 173 | 174 | 175 | 176 | def get_topic(arg): 177 | if not isinstance(arg, str): 178 | raise InvalidTopic(arg) 179 | 180 | if('bnn' in arg): 181 | return bnn_topic() 182 | elif('fairness' in arg): 183 | return fairness_topic() 184 | elif('interpretable' in arg): 185 | return interpretable_topic() 186 | elif('variational' in arg): 187 | return variational_topic() 188 | elif('mcmc' in arg): 189 | return variational_topic() 190 | else: 191 | raise InvalidTopic(arg) 192 | -------------------------------------------------------------------------------- /arxivsearch/utils.py: -------------------------------------------------------------------------------- 1 | import pandas as pd 2 | 3 | 4 | def read_clean_csv(path, sep='|'): 5 | """will read and clean a csv file'""" 6 | df = pd.read_csv(path, sep=sep) 7 | if('Unnamed: 0' in df.columns.values): 8 | df = remove_unnamed(df) 9 | return(df) 10 | 11 | def remove_unnamed(df): 12 | df = df.drop('Unnamed: 0', 1) 13 | return df 14 | -------------------------------------------------------------------------------- /bin/concatenate: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python3 2 | 3 | import feedparser 4 | import datetime 5 | import pandas as pd 6 | 7 | from arxivsearch.topic import topic, get_topic 8 | from arxivsearch.utils import read_clean_csv 9 | 10 | import os 11 | import argparse 12 | import sys 13 | 14 | 15 | def main(arguments): 16 | """ 17 | main() 18 | Description: 19 | Will concatenate the list of papers with the README for this 20 | topic 21 | """ 22 | parser = argparse.ArgumentParser(prog="main", 23 | epilog=main.__doc__) 24 | parser.add_argument('topic', type=str, default='bnn', 25 | help="topic we want to search for") 26 | args = parser.parse_args(arguments) 27 | 28 | #read in the newest data frame search results 29 | new_df = read_clean_csv( 30 | os.path.join('./{}/new_df.csv'.format(args.topic)), sep = '|') 31 | # sometimes an unnamed column is added byu pandas. If it is, remove it 32 | if('Unnamed: 0' in new_df.columns.values): 33 | new_df = remove_unnamed(new_df) 34 | #see if the actual file exists 35 | #if an original readme file exists, lets read it and then prepend 36 | #the data too it 37 | if(os.path.isfile(os.path.join(args.topic, 'readme_df.csv'))): 38 | readme_df = read_clean_csv( 39 | os.path.join(args.topic, 'readme_df.csv'), sep = '|') 40 | # now concatenate the old and new dataframes 41 | # will save this new dataframe at the end 42 | df = pd.concat([new_df, readme_df]) 43 | # now read in the markdown version of the previous search 44 | old_readme = open(os.path.join(args.topic, 'README.md'), 'r') 45 | old_readme_lines = old_readme.readlines() 46 | old_readme.close() 47 | # remove the first two lines of the readme file as this contains the 48 | # title and the instructions, will re-add this in the new markdown file 49 | old_readme_lines = old_readme_lines[2:] 50 | else: 51 | # the new df is the only df, so just set it to that 52 | # will happen when first run 53 | df = new_df 54 | # will create an empty list that will act as mock up of previously read 55 | # data from the Markdown version of search results 56 | old_readme_lines = [' '] * 3 57 | 58 | # create the new README markdown file 59 | # open the file so we can write to it now) 60 | with open(os.path.join(args.topic, 'README.md'), 'w') as f: 61 | # write the topic, instructions and the date 62 | f.write("# " + args.topic + '\nClick on title for link to paper\n') 63 | f.write('## {}\n\n'.format( 64 | datetime.datetime.now().strftime("%d-%m-%Y"))) 65 | # write the new search results 66 | new_df.to_csv(f, index=False, sep='|') 67 | f.write('\n') 68 | # now write the data from the previous search results 69 | for line in old_readme_lines: 70 | f.write(line) 71 | 72 | # from the complete CSV, remove any Nan entries 73 | df = df.dropna() 74 | # now write the new complete dataframe to file so that we can 75 | # use it for our search next time 76 | df.to_csv(os.path.join(args.topic, "readme_df.csv"), 77 | index=False, sep="|", encoding='utf-8') 78 | 79 | if __name__ == "__main__": 80 | sys.exit(main(sys.argv[1:])) 81 | -------------------------------------------------------------------------------- /bin/search: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python3 2 | 3 | import arxivpy 4 | import datetime 5 | import feedparser 6 | import pandas as pd 7 | 8 | from arxivsearch.topic import topic, get_topic 9 | from arxivsearch.utils import read_clean_csv 10 | 11 | import os 12 | import argparse 13 | import sys 14 | 15 | 16 | def format_dataframe(df): 17 | #check to see if the data frame is empty 18 | #if it is, return an empty data frame 19 | if(df.empty): 20 | #set the title and publish date to just say 21 | #no entries for this week 22 | df = pd.DataFrame(data = 23 | {'title':['---', 'No papers found this week'], 24 | 'publish_date':['---', 25 | datetime.datetime.now().strftime("%d-%m-%Y")], 26 | 'main_author':['---', ' ']}) 27 | return df 28 | 29 | #otherwise the dataframe hase some entries and we will format it 30 | df = df.drop(['id', 'terms', 'term', 31 | 'authors', 'abstract', 'comment', 32 | 'journal_ref', 'pdf_url'], axis=1) 33 | #remove repeated entries 34 | df = df.drop_duplicates(subset=['title']) 35 | # sort based on the publish date 36 | df = df.sort_values(by='publish_date', ascending=False) 37 | # now make sure everything is the correct type 38 | types = df.apply(lambda x: pd.api.types.infer_dtype(x.values)) 39 | for col in types[types=='unicode'].index: 40 | df[col] = df[col].apply(lambda x: x.encode('utf-8').strip()) 41 | 42 | df['title'] = df.apply( 43 | lambda row:'[{}]({})'.format(row['title'], 44 | row['url']), axis=1) 45 | df['publish_date'] = df.apply( 46 | lambda row: row['publish_date'].strftime("%d-%m-%Y"), axis=1) 47 | #now drop the unnecesary columns 48 | df = df.drop(['url'], axis=1) 49 | cols = df.columns 50 | # Create a new DataFrame with just the markdown 51 | # strings 52 | df2 = pd.DataFrame([['---',]*len(cols)], columns=cols) 53 | #Create a new concatenated DataFrame 54 | df3 = pd.concat([df2, df]) 55 | return(df3) 56 | 57 | 58 | 59 | def load_prev_search(topic): 60 | """Will load in the previous search results 61 | 62 | If the previous search results aren't around, will 63 | return an dataframe with a single entry with the date from 64 | 60 days ago where it will begin the search, and will remind 65 | you that you are awesome :) 66 | Args: 67 | topic (str): 68 | topic supplied by command line argument 69 | Returns: 70 | Dataframe with the previous search results 71 | """ 72 | df_path = os.path.join('./{}/readme_df.csv'.format(topic)) 73 | if(os.path.isfile(df_path)): 74 | df = read_clean_csv(df_path, sep='|') 75 | else: 76 | start_date = (datetime.datetime.now() - 77 | datetime.timedelta(days = 60)).strftime("%d-%m-%Y") 78 | df = pd.DataFrame(data = 79 | {'title':['---', 'This is where it all Began'], 80 | 'publish_date':['---', start_date], 81 | 'main_author':['---', 'You\'re Awesome!']}) 82 | return(df) 83 | 84 | 85 | 86 | def most_recent_date(prev_df): 87 | """Will return the most recent date from the previous df""" 88 | # put it in a new data frame, as it allows us to find the maximum a 89 | # (most recent date) bit easier 90 | date = pd.DataFrame( 91 | data = {'publish_date': 92 | [datetime.datetime.strptime(d, '%d-%m-%Y') 93 | for d in prev_df.publish_date if (d != '---')]}) 94 | return date.publish_date.max() 95 | 96 | 97 | 98 | def main(arguments): 99 | """ 100 | main() 101 | Description: 102 | Will update the list of papers 103 | """ 104 | parser = argparse.ArgumentParser(prog="main", 105 | epilog=main.__doc__) 106 | parser.add_argument('topic', type=str, default='bnn', 107 | help="topic we want to search for") 108 | 109 | args = parser.parse_args(arguments) 110 | search_topic = get_topic(args.topic) 111 | # get the previous search database 112 | prev_search = load_prev_search(args.topic) 113 | valid_date = most_recent_date(prev_search) 114 | 115 | # get the search terms 116 | search_list = search_topic.format_search() 117 | results = [] 118 | for search in search_list: 119 | results.extend(arxivpy.query(search_query=search)) 120 | 121 | #now wil remove any elements that are older than the specified date 122 | valid_date = valid_date.replace(tzinfo=None) 123 | valid_search = [x for x in results 124 | if (x['publish_date'].date() > valid_date.date())] 125 | 126 | #convert the search results to a df 127 | valid_df = pd.DataFrame(valid_search) 128 | #format the dataframe before we convert it to markdown 129 | markdown_df = format_dataframe(valid_df) 130 | # Save as markdown 131 | # check the folder exists 132 | if(not os.path.isdir(args.topic)): 133 | os.mkdir(args.topic) 134 | markdown_df.to_csv(os.path.join(args.topic, "new_df.csv"), 135 | sep="|", index=False, encoding='utf-8') 136 | 137 | if __name__ == "__main__": 138 | sys.exit(main(sys.argv[1:])) 139 | -------------------------------------------------------------------------------- /bin/update_all: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python3 2 | 3 | import os 4 | import datetime 5 | 6 | if __name__ == "__main__": 7 | for search in ['bnn', 'fairness', 'variational', 'interpretable', 'mcmc']: 8 | os.system('./bin/search ' + search) 9 | os.system('./bin/concatenate ' + search) 10 | os.system('git add ./{}/README.md'.format(search)) 11 | 12 | # add anything else 13 | os.system('git add -u') 14 | # now push it all to git 15 | os.system('git commit -m \" update {} \" '.format( 16 | datetime.datetime.now().strftime("%d-%m-%Y"))) 17 | os.system('git push origin master') 18 | -------------------------------------------------------------------------------- /causal/README.md: -------------------------------------------------------------------------------- 1 | # Causal Inference 2 | 3 | For an excellent list of recent papers relating to causal inference, please refer to the [arXausality](https://github.com/logangraham/arxausality) 4 | repository by [Logan Graham](http://logangraham.xyz/) -------------------------------------------------------------------------------- /interpretable/README.md: -------------------------------------------------------------------------------- 1 | # interpretable 2 | Click on title for link to paper 3 | ## 20-06-2023 4 | 5 | main_author|title|update_date|publish_date 6 | ---|---|---|--- 7 | Özgür Şimşek|[Explaining Reinforcement Learning with Shapley Values](http://arxiv.org/abs/2306.05810v1)|2023-06-09 10:52:39+00:00|09-06-2023 8 | Dacheng Tao|[Understanding How Consistency Works in Federated Learning via Stage-wise Relaxed Initialization](http://arxiv.org/abs/2306.05706v1)|2023-06-09 06:55:15+00:00|09-06-2023 9 | Ion Stoica|[Judging LLM-as-a-judge with MT-Bench and Chatbot Arena](http://arxiv.org/abs/2306.05685v1)|2023-06-09 05:55:52+00:00|09-06-2023 10 | Kun Zhang|[Understanding Masked Autoencoders via Hierarchical Latent Variable Models](http://arxiv.org/abs/2306.04898v1)|2023-06-08 03:00:10+00:00|08-06-2023 11 | Been Kim|[Don't trust your eyes: on the (un)reliability of feature visualizations](http://arxiv.org/abs/2306.04719v1)|2023-06-07 18:31:39+00:00|07-06-2023 12 | Gabriel Loaiza-Ganem|[Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models](http://arxiv.org/abs/2306.04675v1)|2023-06-07 18:00:00+00:00|07-06-2023 13 | Michiaki Tatsubori|[Utterance Classification with Logical Neural Network: Explainable AI for Mental Disorder Diagnosis](http://arxiv.org/abs/2306.03902v1)|2023-06-06 17:58:44+00:00|06-06-2023 14 | Julia E. Vogt|[(Un)reasonable Allure of Ante-hoc Interpretability for High-stakes Domains: Transparency Is Necessary but Insufficient for Explainability](http://arxiv.org/abs/2306.02312v1)|2023-06-04 09:34:41+00:00|04-06-2023 15 | Rebecca L. Davis|[Mitigating Molecular Aggregation in Drug Discovery with Predictive Insights from Explainable AI](http://arxiv.org/abs/2306.02206v1)|2023-06-03 22:30:45+00:00|03-06-2023 16 | Maarten Sap|[COBRA Frames: Contextual Reasoning about Effects and Harms of Offensive Statements](http://arxiv.org/abs/2306.01985v2)|2023-06-09 01:49:06+00:00|03-06-2023 17 | 18 | ## 13-06-2023 19 | 20 | main_author|title|update_date|publish_date 21 | ---|---|---|--- 22 | Özgür Şimşek|[Explaining Reinforcement Learning with Shapley Values](http://arxiv.org/abs/2306.05810v1)|2023-06-09 10:52:39+00:00|09-06-2023 23 | Dacheng Tao|[Understanding How Consistency Works in Federated Learning via Stage-wise Relaxed Initialization](http://arxiv.org/abs/2306.05706v1)|2023-06-09 06:55:15+00:00|09-06-2023 24 | Ion Stoica|[Judging LLM-as-a-judge with MT-Bench and Chatbot Arena](http://arxiv.org/abs/2306.05685v1)|2023-06-09 05:55:52+00:00|09-06-2023 25 | Kun Zhang|[Understanding Masked Autoencoders via Hierarchical Latent Variable Models](http://arxiv.org/abs/2306.04898v1)|2023-06-08 03:00:10+00:00|08-06-2023 26 | Been Kim|[Don't trust your eyes: on the (un)reliability of feature visualizations](http://arxiv.org/abs/2306.04719v1)|2023-06-07 18:31:39+00:00|07-06-2023 27 | Gabriel Loaiza-Ganem|[Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models](http://arxiv.org/abs/2306.04675v1)|2023-06-07 18:00:00+00:00|07-06-2023 28 | Michiaki Tatsubori|[Utterance Classification with Logical Neural Network: Explainable AI for Mental Disorder Diagnosis](http://arxiv.org/abs/2306.03902v1)|2023-06-06 17:58:44+00:00|06-06-2023 29 | Julia E. Vogt|[(Un)reasonable Allure of Ante-hoc Interpretability for High-stakes Domains: Transparency Is Necessary but Insufficient for Explainability](http://arxiv.org/abs/2306.02312v1)|2023-06-04 09:34:41+00:00|04-06-2023 30 | Rebecca L. Davis|[Mitigating Molecular Aggregation in Drug Discovery with Predictive Insights from Explainable AI](http://arxiv.org/abs/2306.02206v1)|2023-06-03 22:30:45+00:00|03-06-2023 31 | Maarten Sap|[COBRA Frames: Contextual Reasoning about Effects and Harms of Offensive Statements](http://arxiv.org/abs/2306.01985v2)|2023-06-09 01:49:06+00:00|03-06-2023 32 | 33 | ## 06-06-2023 34 | 35 | main_author|title|update_date|publish_date 36 | ---|---|---|--- 37 | Sujith K Mandala|[XAI Renaissance: Redefining Interpretability in Medical Diagnostic Models](http://arxiv.org/abs/2306.01668v1)|2023-06-02 16:42:20+00:00|02-06-2023 38 | Soumia Zohra El Mestari|[The Flawed Foundations of Fair Machine Learning](http://arxiv.org/abs/2306.01417v1)|2023-06-02 10:07:12+00:00|02-06-2023 39 | Halil Kilicoglu|[Examining the Causal Effect of First Names on Language Models: The Case of Social Commonsense Reasoning](http://arxiv.org/abs/2306.01117v1)|2023-06-01 20:05:05+00:00|01-06-2023 40 | Boris Babenko|[Using generative AI to investigate medical imagery models and datasets](http://arxiv.org/abs/2306.00985v1)|2023-06-01 17:59:55+00:00|01-06-2023 41 | Anders Søgaard|[Being Right for Whose Right Reasons?](http://arxiv.org/abs/2306.00639v1)|2023-06-01 13:06:43+00:00|01-06-2023 42 | Ofir Lindenbaum|[Neuronal Cell Type Classification using Deep Learning](http://arxiv.org/abs/2306.00528v1)|2023-06-01 10:28:49+00:00|01-06-2023 43 | Gordon L Kindlmann|[Evaluating Machine Learning Models with NERO: Non-Equivariance Revealed on Orbits](http://arxiv.org/abs/2305.19889v1)|2023-05-31 14:24:35+00:00|31-05-2023 44 | Derek F. Wong|[How Does Pretraining Improve Discourse-Aware Translation?](http://arxiv.org/abs/2305.19847v1)|2023-05-31 13:36:51+00:00|31-05-2023 45 | Seong Joon Oh|[A Bayesian Perspective On Training Data Attribution](http://arxiv.org/abs/2305.19765v1)|2023-05-31 11:52:20+00:00|31-05-2023 46 | Jiebo Luo|[Unveiling Cross Modality Bias in Visual Question Answering: A Causal View with Possible Worlds VQA](http://arxiv.org/abs/2305.19664v1)|2023-05-31 09:02:58+00:00|31-05-2023 47 | Hima Lakkaraju|[Which Models have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness](http://arxiv.org/abs/2305.19101v1)|2023-05-30 15:06:02+00:00|30-05-2023 48 | Guannan Zhang|[Who Would be Interested in Services? An Entity Graph Learning System for User Targeting](http://arxiv.org/abs/2305.18780v1)|2023-05-30 06:24:50+00:00|30-05-2023 49 | Bonnie J. Dorr|[LonXplain: Lonesomeness as a Consequence of Mental Disturbance in Reddit Posts](http://arxiv.org/abs/2305.18736v1)|2023-05-30 04:21:24+00:00|30-05-2023 50 | Franco Turini|[Reason to explain: Interactive contrastive explanations (REASONX)](http://arxiv.org/abs/2305.18143v1)|2023-05-29 15:13:46+00:00|29-05-2023 51 | Ajitha Rajan|[Can We Trust Explainable AI Methods on ASR? An Evaluation on Phoneme Recognition](http://arxiv.org/abs/2305.18011v1)|2023-05-29 11:04:13+00:00|29-05-2023 52 | Naoki Abe|[Black-Box Anomaly Attribution](http://arxiv.org/abs/2305.18440v1)|2023-05-29 01:42:32+00:00|29-05-2023 53 | Xinyu Yang|[Learning a Structural Causal Model for Intuition Reasoning in Conversation](http://arxiv.org/abs/2305.17727v1)|2023-05-28 13:54:09+00:00|28-05-2023 54 | Roy Ka-Wei Lee|[Decoding the Underlying Meaning of Multimodal Hateful Memes](http://arxiv.org/abs/2305.17678v1)|2023-05-28 10:02:59+00:00|28-05-2023 55 | Eric V. Strobl|[Counterfactual Formulation of Patient-Specific Root Causes of Disease](http://arxiv.org/abs/2305.17574v2)|2023-05-31 22:16:20+00:00|27-05-2023 56 | Jun Sakuma|[Statistically Significant Concept-based Explanation of Image Classifiers via Model Knockoffs](http://arxiv.org/abs/2305.18362v2)|2023-05-31 03:20:18+00:00|27-05-2023 57 | Haifeng Chen|[DNA-GPT: Divergent N-Gram Analysis for Training-Free Detection of GPT-Generated Text](http://arxiv.org/abs/2305.17359v1)|2023-05-27 03:58:29+00:00|27-05-2023 58 | 59 | ## 30-05-2023 60 | 61 | main_author|title|update_date|publish_date 62 | ---|---|---|--- 63 | Manfred K. Warmuth|[A Mechanism for Sample-Efficient In-Context Learning for Sparse Retrieval Tasks](http://arxiv.org/abs/2305.17040v1)|2023-05-26 15:49:43+00:00|26-05-2023 64 | Fisher Yu|[How To Not Train Your Dragon: Training-free Embodied Object Goal Navigation with Semantic Frontiers](http://arxiv.org/abs/2305.16925v1)|2023-05-26 13:38:33+00:00|26-05-2023 65 | Tal Kachman|[Explainability Techniques for Chemical Language Models](http://arxiv.org/abs/2305.16192v1)|2023-05-25 15:52:54+00:00|25-05-2023 66 | Christophe De Vleeschouwer|[An Experimental Investigation into the Evaluation of Explainability Methods](http://arxiv.org/abs/2305.16361v1)|2023-05-25 08:07:07+00:00|25-05-2023 67 | Theodore P. Pavlic|[Concept-Centric Transformers: Concept Transformers with Object-Centric Concept Learning for Interpretability](http://arxiv.org/abs/2305.15775v1)|2023-05-25 06:37:39+00:00|25-05-2023 68 | Shuming Shi|[Enhancing Grammatical Error Correction Systems with Explanations](http://arxiv.org/abs/2305.15676v1)|2023-05-25 03:00:49+00:00|25-05-2023 69 | Lei Hou|[Reasoning over Hierarchical Question Decomposition Tree for Explainable Question Answering](http://arxiv.org/abs/2305.15056v1)|2023-05-24 11:45:59+00:00|24-05-2023 70 | Philippe Blanc|[Scale Matters: Attribution Meets the Wavelet Domain to Explain Model Sensitivity to Image Corruptions](http://arxiv.org/abs/2305.14979v1)|2023-05-24 10:13:32+00:00|24-05-2023 71 | Manabu Okumura|[TACR: A Table-alignment-based Cell-selection and Reasoning Model for Hybrid Question-Answering](http://arxiv.org/abs/2305.14682v1)|2023-05-24 03:42:44+00:00|24-05-2023 72 | Smaranda Muresan|[Sociocultural Norm Similarities and Differences via Situational Alignment and Explainable Textual Entailment](http://arxiv.org/abs/2305.14492v1)|2023-05-23 19:43:47+00:00|23-05-2023 73 | Alexander M. Rush|[HOP, UNION, GENERATE: Explainable Multi-hop Reasoning without Rationale Supervision](http://arxiv.org/abs/2305.14237v1)|2023-05-23 16:53:49+00:00|23-05-2023 74 | Parisa Kordjamshidi|[Teaching Probabilistic Logical Reasoning to Transformers](http://arxiv.org/abs/2305.13179v1)|2023-05-22 16:08:20+00:00|22-05-2023 75 | Andreas Vlachos|[AVeriTeC: A Dataset for Real-world Claim Verification with Evidence from the Web](http://arxiv.org/abs/2305.13117v2)|2023-05-24 10:44:08+00:00|22-05-2023 76 | Shashank Srivastava|[MaNtLE: Model-agnostic Natural Language Explainer](http://arxiv.org/abs/2305.12995v1)|2023-05-22 12:58:06+00:00|22-05-2023 77 | Xia Hu|[DEGREE: Decomposition Based Explanation For Graph Neural Networks](http://arxiv.org/abs/2305.12895v1)|2023-05-22 10:29:52+00:00|22-05-2023 78 | Heng Ji|[In-Context Learning of Large Language Models Explained as Kernel Regression](http://arxiv.org/abs/2305.12766v1)|2023-05-22 06:45:02+00:00|22-05-2023 79 | Weihua Zhou|[Coronary Artery Semantic Labeling using Edge Attention Graph Matching Network](http://arxiv.org/abs/2305.12327v1)|2023-05-21 03:14:42+00:00|21-05-2023 80 | Peter McBurney|[A Measure of Explanatory Effectiveness](http://arxiv.org/abs/2305.12233v1)|2023-05-20 16:52:30+00:00|20-05-2023 81 | 82 | ## 23-05-2023 83 | 84 | main_author|title|update_date|publish_date 85 | ---|---|---|--- 86 | Long Chen|[TreePrompt: Learning to Compose Tree Prompts for Explainable Visual Grounding](http://arxiv.org/abs/2305.11497v1)|2023-05-19 07:52:22+00:00|19-05-2023 87 | Zhoulai Fu|[In Defense of Pure 16-bit Floating-Point Neural Networks](http://arxiv.org/abs/2305.10947v1)|2023-05-18 13:09:45+00:00|18-05-2023 88 | Mihael Mohorčič|[XAI for Self-supervised Clustering of Wireless Spectrum Activity](http://arxiv.org/abs/2305.10060v1)|2023-05-17 08:56:43+00:00|17-05-2023 89 | Shane Steinert-Threlkeld|[The Weighted Möbius Score: A Unified Framework for Feature Attribution](http://arxiv.org/abs/2305.09204v1)|2023-05-16 06:27:27+00:00|16-05-2023 90 | Manoj Tiwari|[Leveraging Large Language Models in Conversational Recommender Systems](http://arxiv.org/abs/2305.07961v2)|2023-05-16 21:21:46+00:00|13-05-2023 91 | 92 | ## 16-05-2023 93 | 94 | main_author|title|update_date|publish_date 95 | ---|---|---|--- 96 | Haoliang Li|[Interpretable Multimodal Misinformation Detection with Logic Reasoning](http://arxiv.org/abs/2305.05964v1)|2023-05-10 08:16:36+00:00|10-05-2023 97 | Yulan He|[Explainable Recommender with Geometric Information Bottleneck](http://arxiv.org/abs/2305.05331v1)|2023-05-09 10:38:36+00:00|09-05-2023 98 | Adnan Darwiche|[Logic for Explainable AI](http://arxiv.org/abs/2305.05172v1)|2023-05-09 04:53:57+00:00|09-05-2023 99 | Rosina O Weber|[When a CBR in Hand is Better than Twins in the Bush](http://arxiv.org/abs/2305.05111v1)|2023-05-09 00:55:09+00:00|09-05-2023 100 | Amit Sheth|[Knowledge Graph Guided Semantic Evaluation of Language Models For User Trust](http://arxiv.org/abs/2305.04989v1)|2023-05-08 18:53:14+00:00|08-05-2023 101 | Giri Narasimhan|[Explainable Parallel RCNN with Novel Feature Representation for Time Series Forecasting](http://arxiv.org/abs/2305.04876v1)|2023-05-08 17:20:13+00:00|08-05-2023 102 | Senja Pollak|[XAI in Computational Linguistics: Understanding Political Leanings in the Slovenian Parliament](http://arxiv.org/abs/2305.04631v1)|2023-05-08 11:19:21+00:00|08-05-2023 103 | Samuel R. Bowman|[Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting](http://arxiv.org/abs/2305.04388v1)|2023-05-07 22:44:25+00:00|07-05-2023 104 | Bart Goethals|[Efficient pattern-based anomaly detection in a network of multivariate devices](http://arxiv.org/abs/2305.05538v1)|2023-05-07 16:05:30+00:00|07-05-2023 105 | Bruno Petrungaro|[Open problems in causal structure learning: A case study of COVID-19 in the UK](http://arxiv.org/abs/2305.03859v1)|2023-05-05 22:04:00+00:00|05-05-2023 106 | 107 | ## 09-05-2023 108 | 109 | main_author|title|update_date|publish_date 110 | ---|---|---|--- 111 | Meisam Razaviyayn|[Distributing Synergy Functions: Unifying Game-Theoretic Interaction Methods for Machine-Learning Explainability](http://arxiv.org/abs/2305.03100v1)|2023-05-04 18:33:18+00:00|04-05-2023 112 | Matthias Samwald|[An automatically discovered chain-of-thought prompt generalizes to novel models and datasets](http://arxiv.org/abs/2305.02897v1)|2023-05-04 15:07:20+00:00|04-05-2023 113 | Cristian Tufisi|[Neuro-symbolic model for cantilever beams damage detection](http://arxiv.org/abs/2305.03063v1)|2023-05-04 13:12:39+00:00|04-05-2023 114 | Claire Cardie|[Fashionpedia-Taste: A Dataset towards Explaining Human Fashion Taste](http://arxiv.org/abs/2305.02307v1)|2023-05-03 17:54:50+00:00|03-05-2023 115 | Cecilia Sonstrod|[Calibrated Explanations: with Uncertainty Information and Counterfactuals](http://arxiv.org/abs/2305.02305v1)|2023-05-03 17:52:41+00:00|03-05-2023 116 | Tan Wang|[Explaining Language Models' Predictions with High-Impact Concepts](http://arxiv.org/abs/2305.02160v1)|2023-05-03 14:48:27+00:00|03-05-2023 117 | Ulrike Lohmann|[Understanding cirrus clouds using explainable machine learning](http://arxiv.org/abs/2305.02090v1)|2023-05-03 12:50:57+00:00|03-05-2023 118 | Karim Lekadir|[Commentary on explainable artificial intelligence methods: SHAP and LIME](http://arxiv.org/abs/2305.02012v2)|2023-05-08 11:09:07+00:00|03-05-2023 119 | Christopher Naugler|[Automated Paper Screening for Clinical Reviews Using Large Language Models](http://arxiv.org/abs/2305.00844v1)|2023-05-01 14:16:37+00:00|01-05-2023 120 | Marcel Worring|[Causalainer: Causal Explainer for Automatic Video Summarization](http://arxiv.org/abs/2305.00455v1)|2023-04-30 11:42:06+00:00|30-04-2023 121 | 122 | ## 02-05-2023 123 | 124 | main_author|title|update_date|publish_date 125 | ---|---|---|--- 126 | Adnan Darwiche|[A New Class of Explanations for Classifiers with Non-Binary Features](http://arxiv.org/abs/2304.14760v1)|2023-04-28 11:05:46+00:00|28-04-2023 127 | Naser Damer|[Efficient Explainable Face Verification based on Similarity Score Argument Backpropagation](http://arxiv.org/abs/2304.13409v1)|2023-04-26 09:48:48+00:00|26-04-2023 128 | Bhaktee Dongaonkar|[Towards Explainable and Safe Conversational Agents for Mental Health: A Survey](http://arxiv.org/abs/2304.13191v1)|2023-04-25 23:12:13+00:00|25-04-2023 129 | Stefan Wermter|[A Closer Look at Reward Decomposition for High-Level Robotic Explanations](http://arxiv.org/abs/2304.12958v1)|2023-04-25 16:01:42+00:00|25-04-2023 130 | Marie-Catherine de Marneffe|[Understanding and Predicting Human Label Variation in Natural Language Inference through Explanation](http://arxiv.org/abs/2304.12443v1)|2023-04-24 20:45:09+00:00|24-04-2023 131 | Tim Fingscheidt|[Survey on Unsupervised Domain Adaptation for Semantic Segmentation for Visual Perception in Automated Driving](http://arxiv.org/abs/2304.11928v1)|2023-04-24 09:13:23+00:00|24-04-2023 132 | Rich Caruana|[Missing Values and Imputation in Healthcare Data: Can Interpretable Machine Learning Help?](http://arxiv.org/abs/2304.11749v1)|2023-04-23 20:54:47+00:00|23-04-2023 133 | Jaesik Choi|[The Disharmony Between BN and ReLU Causes Gradient Explosion, but is Offset by the Correlation Between Activations](http://arxiv.org/abs/2304.11692v2)|2023-04-27 10:14:48+00:00|23-04-2023 134 | Manjot Singh|[An Efficient Ensemble Explainable AI (XAI) Approach for Morphed Face Detection](http://arxiv.org/abs/2304.14509v1)|2023-04-23 13:43:06+00:00|23-04-2023 135 | Shikun Zhang|[Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness](http://arxiv.org/abs/2304.11633v1)|2023-04-23 12:33:18+00:00|23-04-2023 136 | 137 | ## 25-04-2023 138 | 139 | main_author|title|update_date|publish_date 140 | ---|---|---|--- 141 | Timothy Proctor|[Learning a quantum computer's capability using convolutional neural networks](http://arxiv.org/abs/2304.10650v1)|2023-04-20 21:25:33+00:00|20-04-2023 142 | Henk de Regt|[Towards a Benchmark for Scientific Understanding in Humans and Machines](http://arxiv.org/abs/2304.10327v2)|2023-04-21 08:57:06+00:00|20-04-2023 143 | Georgina Cosma|[A Meta-heuristic Approach to Estimate and Explain Classifier Uncertainty](http://arxiv.org/abs/2304.10284v1)|2023-04-20 13:09:28+00:00|20-04-2023 144 | Klaus-Robert Müller|[Towards transparent and robust data-driven wind turbine power curve models](http://arxiv.org/abs/2304.09835v1)|2023-04-19 17:37:58+00:00|19-04-2023 145 | 146 | ## 18-04-2023 147 | 148 | main_author|title|update_date|publish_date 149 | ---|---|---|--- 150 | My T. Thai|[Cultural-aware Machine Learning based Analysis of COVID-19 Vaccine Hesitancy](http://arxiv.org/abs/2304.06953v1)|2023-04-14 06:47:43+00:00|14-04-2023 151 | Xiaoying Tang|[MProtoNet: A Case-Based Interpretable Model for Brain Tumor Classification with 3D Multi-parametric Magnetic Resonance Imaging](http://arxiv.org/abs/2304.06258v2)|2023-04-14 15:51:54+00:00|13-04-2023 152 | Xiaomeng Li|[CLIP Surgery for Better Explainability with Enhancement in Open-Vocabulary Tasks](http://arxiv.org/abs/2304.05653v1)|2023-04-12 07:16:55+00:00|12-04-2023 153 | Qiang Ji|[Gradient-based Uncertainty Attribution for Explainable Bayesian Deep Learning](http://arxiv.org/abs/2304.04824v1)|2023-04-10 19:14:15+00:00|10-04-2023 154 | Manish Shrivastava|[Attention at SemEval-2023 Task 10: Explainable Detection of Online Sexism (EDOS)](http://arxiv.org/abs/2304.04610v1)|2023-04-10 14:24:52+00:00|10-04-2023 155 | Bo Yang|[Pretrained Embeddings for E-commerce Machine Learning: When it Fails and Why?](http://arxiv.org/abs/2304.04330v1)|2023-04-09 23:55:47+00:00|09-04-2023 156 | Christian Daul|[Deep Prototypical-Parts Ease Morphological Kidney Stone Identification and are Competitively Robust to Photometric Perturbations](http://arxiv.org/abs/2304.04077v1)|2023-04-08 17:43:31+00:00|08-04-2023 157 | Arto Hellas|[Comparing Code Explanations Created by Students and Large Language Models](http://arxiv.org/abs/2304.03938v1)|2023-04-08 06:52:54+00:00|08-04-2023 158 | Sebastian Schuster|[Expectations over Unspoken Alternatives Predict Pragmatic Inferences](http://arxiv.org/abs/2304.04758v1)|2023-04-07 18:12:22+00:00|07-04-2023 159 | 160 | ## 11-04-2023 161 | 162 | main_author|title|update_date|publish_date 163 | ---|---|---|--- 164 | Sophia Ananiadou|[On the Evaluations of ChatGPT and Emotion-enhanced Prompting for Mental Health Analysis](http://arxiv.org/abs/2304.03347v1)|2023-04-06 19:53:59+00:00|06-04-2023 165 | Yves Le Traon|[Going Further: Flatness at the Rescue of Early Stopping for Adversarial Example Transferability](http://arxiv.org/abs/2304.02688v1)|2023-04-05 18:31:25+00:00|05-04-2023 166 | Clinton Fookes|[Towards Self-Explainability of Deep Neural Networks with Heatmap Captioning and Large-Language Models](http://arxiv.org/abs/2304.02202v1)|2023-04-05 03:29:37+00:00|05-04-2023 167 | Daniel Sonntag|[Fine-tuning of explainable CNNs for skin lesion classification based on dermatologists' feedback towards increasing trust](http://arxiv.org/abs/2304.01399v1)|2023-04-03 22:30:08+00:00|03-04-2023 168 | Yohai Bar-Sinai|[Charting the Topography of the Neural Network Landscape with Thermal-Like Noise](http://arxiv.org/abs/2304.01335v1)|2023-04-03 20:01:52+00:00|03-04-2023 169 | Pedram Ghamisi|[Dsfer-Net: A Deep Supervision and Feature Retrieval Network for Bitemporal Change Detection Using Modern Hopfield Networks](http://arxiv.org/abs/2304.01101v1)|2023-04-03 16:01:03+00:00|03-04-2023 170 | Quanshi Zhang|[Can the Inference Logic of Large Language Models be Disentangled into Symbolic Concepts?](http://arxiv.org/abs/2304.01083v1)|2023-04-03 15:39:35+00:00|03-04-2023 171 | Wei Liu|[Evaluating Large Language Models on a Highly-specialized Topic, Radiation Oncology Physics](http://arxiv.org/abs/2304.01938v1)|2023-04-01 06:04:58+00:00|01-04-2023 172 | 173 | ## 04-04-2023 174 | 175 | main_author|title|update_date|publish_date 176 | ---|---|---|--- 177 | Leonidas Guibas|[VDN-NeRF: Resolving Shape-Radiance Ambiguity via View-Dependence Normalization](http://arxiv.org/abs/2303.17968v1)|2023-03-31 11:13:17+00:00|31-03-2023 178 | Maria Seale|[Explainable Intrusion Detection Systems Using Competitive Learning Techniques](http://arxiv.org/abs/2303.17387v1)|2023-03-30 13:58:47+00:00|30-03-2023 179 | Misha Sra|[LMExplainer: a Knowledge-Enhanced Explainer for Language Models](http://arxiv.org/abs/2303.16537v1)|2023-03-29 08:59:44+00:00|29-03-2023 180 | Nicolas Chesneau|[Evaluating self-attention interpretability through human-grounded experimental protocol](http://arxiv.org/abs/2303.15190v1)|2023-03-27 13:26:02+00:00|27-03-2023 181 | Mohsen Jahanshahi|[Farspredict: A benchmark dataset for link prediction](http://arxiv.org/abs/2303.14647v1)|2023-03-26 07:41:26+00:00|26-03-2023 182 | Mohammad Rostami|[Explainable Artificial Intelligence Architecture for Melanoma Diagnosis Using Indicator Localization and Self-Supervised Learning](http://arxiv.org/abs/2303.14615v1)|2023-03-26 03:43:05+00:00|26-03-2023 183 | Jun Ni|[Shapley-based Explainable AI for Clustering Applications in Fault Diagnosis and Prognosis](http://arxiv.org/abs/2303.14581v1)|2023-03-25 23:13:11+00:00|25-03-2023 184 | 185 | ## 28-03-2023 186 | 187 | main_author|title|update_date|publish_date 188 | ---|---|---|--- 189 | Nassir Navab|[Xplainer: From X-Ray Observations to Explainable Zero-Shot Diagnosis](http://arxiv.org/abs/2303.13391v2)|2023-03-27 11:36:12+00:00|23-03-2023 190 | Ghulam Rasool|[Revisiting the Fragility of Influence Functions](http://arxiv.org/abs/2303.12922v1)|2023-03-22 21:36:56+00:00|22-03-2023 191 | Quanming Yao|[Logical Expressiveness of Graph Neural Network for Knowledge Graph Reasoning](http://arxiv.org/abs/2303.12306v1)|2023-03-22 04:49:00+00:00|22-03-2023 192 | Rongrong Ji|[Solving Oscillation Problem in Post-Training Quantization Through a Theoretical Perspective](http://arxiv.org/abs/2303.11906v1)|2023-03-21 14:52:52+00:00|21-03-2023 193 | Kai Fong Ernest Chong|[Abstract Visual Reasoning: An Algebraic Approach for Solving Raven's Progressive Matrices](http://arxiv.org/abs/2303.11730v1)|2023-03-21 10:34:39+00:00|21-03-2023 194 | Nitish Shukla|[An Embarrassingly Simple Approach for Wafer Feature Extraction and Defect Pattern Recognition](http://arxiv.org/abs/2303.11632v1)|2023-03-21 07:00:13+00:00|21-03-2023 195 | Eric Horvitz|[Capabilities of GPT-4 on Medical Challenge Problems](http://arxiv.org/abs/2303.13375v1)|2023-03-20 16:18:38+00:00|20-03-2023 196 | Pierre Borgnat|[Studying Limits of Explainability by Integrated Gradients for Gene Expression Models](http://arxiv.org/abs/2303.11336v1)|2023-03-19 19:54:15+00:00|19-03-2023 197 | Titus J. Brinker|[Dermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma](http://arxiv.org/abs/2303.12806v1)|2023-03-17 17:25:55+00:00|17-03-2023 198 | Przemysław Biecek|[Hospital Length of Stay Prediction Based on Multi-modal Data towards Trustworthy Human-AI Collaboration in Radiomics](http://arxiv.org/abs/2303.09817v1)|2023-03-17 07:53:18+00:00|17-03-2023 199 | Wenwen Li|[Explainable GeoAI: Can saliency maps help interpret artificial intelligence's learning process? An empirical study on natural feature detection](http://arxiv.org/abs/2303.09660v1)|2023-03-16 21:37:29+00:00|16-03-2023 200 | Eoin Delaney|[Explaining Groups of Instances Counterfactually for XAI: A Use Case, Algorithm and User Study for Group-Counterfactuals](http://arxiv.org/abs/2303.09297v1)|2023-03-16 13:16:50+00:00|16-03-2023 201 | Carsten Marr|[Pixel-Level Explanation of Multiple Instance Learning Models in Biomedical Single Cell Images](http://arxiv.org/abs/2303.08632v1)|2023-03-15 14:00:11+00:00|15-03-2023 202 | MohammadMehdi Homayounpour|[Explaining Recommendation System Using Counterfactual Textual Explanations](http://arxiv.org/abs/2303.11160v1)|2023-03-14 06:45:28+00:00|14-03-2023 203 | Xiaohui Yuan|[Designing Deep Networks for Scene Recognition](http://arxiv.org/abs/2303.07402v1)|2023-03-13 18:28:06+00:00|13-03-2023 204 | Roy Schwartz|[Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images](http://arxiv.org/abs/2303.07274v2)|2023-03-14 21:30:06+00:00|13-03-2023 205 | Przemyslaw Biecek|[Challenges facing the explainability of age prediction models: case study for two modalities](http://arxiv.org/abs/2303.06640v1)|2023-03-12 11:51:21+00:00|12-03-2023 206 | Mingli Song|[Schema Inference for Interpretable Image Classification](http://arxiv.org/abs/2303.06635v1)|2023-03-12 11:23:56+00:00|12-03-2023 207 | 208 | ## 21-03-2023 209 | 210 | main_author|title|update_date|publish_date 211 | ---|---|---|--- 212 | Yuliang Liu|[New Benchmarks for Accountable Text-based Visual Re-creation](http://arxiv.org/abs/2303.05983v1)|2023-03-10 15:35:11+00:00|10-03-2023 213 | Liz Sonenberg|[Explaining Model Confidence Using Counterfactuals](http://arxiv.org/abs/2303.05729v1)|2023-03-10 06:22:13+00:00|10-03-2023 214 | Joaquín Borrego-Díaz|[On the Soundness of XAI in Prognostics and Health Management (PHM)](http://arxiv.org/abs/2303.05517v1)|2023-03-09 13:27:54+00:00|09-03-2023 215 | Mohammed Bennamoun|[Analysis and Evaluation of Explainable Artificial Intelligence on Suicide Risk Assessment](http://arxiv.org/abs/2303.06052v1)|2023-03-09 05:11:46+00:00|09-03-2023 216 | Quoc Khanh Nguyen|[Towards Trust of Explainable AI in Thyroid Nodule Diagnosis](http://arxiv.org/abs/2303.04731v1)|2023-03-08 17:18:13+00:00|08-03-2023 217 | Andreas Gregoriades|"[""How to make them stay?"" -- Diverse Counterfactual Explanations of Employee Attrition](http://arxiv.org/abs/2303.04579v1)"|2023-03-08 13:54:57+00:00|08-03-2023 218 | Houbing Song|[Exploring Adversarial Attacks on Neural Networks: An Explainable Approach](http://arxiv.org/abs/2303.06032v1)|2023-03-08 07:59:44+00:00|08-03-2023 219 | Ignasi Cos|[A topological classifier to characterize brain states: When shape matters more than variance](http://arxiv.org/abs/2303.04231v1)|2023-03-07 20:45:15+00:00|07-03-2023 220 | Yufei Yu|[Multi-resolution Interpretation and Diagnostics Tool for Natural Language Classifiers](http://arxiv.org/abs/2303.03542v1)|2023-03-06 22:59:02+00:00|06-03-2023 221 | Ummar Abbas|[NxPlain: Web-based Tool for Discovery of Latent Concepts](http://arxiv.org/abs/2303.03019v1)|2023-03-06 10:45:24+00:00|06-03-2023 222 | Leopoldo Bertossi|[Attribution-Scores and Causal Counterfactuals as Explanations in Artificial Intelligence](http://arxiv.org/abs/2303.02829v1)|2023-03-06 01:46:51+00:00|06-03-2023 223 | Giorgos Stamou|[Knowledge-Based Counterfactual Queries for Visual Question Answering](http://arxiv.org/abs/2303.02601v1)|2023-03-05 08:00:30+00:00|05-03-2023 224 | 225 | ## 14-03-2023 226 | 227 | main_author|title|update_date|publish_date 228 | ---|---|---|--- 229 | Yuliang Liu|[New Benchmarks for Accountable Text-based Visual Re-creation](http://arxiv.org/abs/2303.05983v1)|2023-03-10 15:35:11+00:00|10-03-2023 230 | Liz Sonenberg|[Explaining Model Confidence Using Counterfactuals](http://arxiv.org/abs/2303.05729v1)|2023-03-10 06:22:13+00:00|10-03-2023 231 | Joaquín Borrego-Díaz|[On the Soundness of XAI in Prognostics and Health Management (PHM)](http://arxiv.org/abs/2303.05517v1)|2023-03-09 13:27:54+00:00|09-03-2023 232 | Mohammed Bennamoun|[Analysis and Evaluation of Explainable Artificial Intelligence on Suicide Risk Assessment](http://arxiv.org/abs/2303.06052v1)|2023-03-09 05:11:46+00:00|09-03-2023 233 | Quoc Khanh Nguyen|[Towards Trust of Explainable AI in Thyroid Nodule Diagnosis](http://arxiv.org/abs/2303.04731v1)|2023-03-08 17:18:13+00:00|08-03-2023 234 | Andreas Gregoriades|"[""How to make them stay?"" -- Diverse Counterfactual Explanations of Employee Attrition](http://arxiv.org/abs/2303.04579v1)"|2023-03-08 13:54:57+00:00|08-03-2023 235 | Houbing Song|[Exploring Adversarial Attacks on Neural Networks: An Explainable Approach](http://arxiv.org/abs/2303.06032v1)|2023-03-08 07:59:44+00:00|08-03-2023 236 | Ignasi Cos|[A topological classifier to characterize brain states: When shape matters more than variance](http://arxiv.org/abs/2303.04231v1)|2023-03-07 20:45:15+00:00|07-03-2023 237 | Yufei Yu|[Multi-resolution Interpretation and Diagnostics Tool for Natural Language Classifiers](http://arxiv.org/abs/2303.03542v1)|2023-03-06 22:59:02+00:00|06-03-2023 238 | Ummar Abbas|[NxPlain: Web-based Tool for Discovery of Latent Concepts](http://arxiv.org/abs/2303.03019v1)|2023-03-06 10:45:24+00:00|06-03-2023 239 | Leopoldo Bertossi|[Attribution-Scores and Causal Counterfactuals as Explanations in Artificial Intelligence](http://arxiv.org/abs/2303.02829v1)|2023-03-06 01:46:51+00:00|06-03-2023 240 | Giorgos Stamou|[Knowledge-Based Counterfactual Queries for Visual Question Answering](http://arxiv.org/abs/2303.02601v1)|2023-03-05 08:00:30+00:00|05-03-2023 241 | 242 | ## 07-03-2023 243 | 244 | main_author|title|update_date|publish_date 245 | ---|---|---|--- 246 | Effrosyni Kokiopoulou|[When does Privileged Information Explain Away Label Noise?](http://arxiv.org/abs/2303.01806v1)|2023-03-03 09:25:39+00:00|03-03-2023 247 | Jin Keun Seo|[Nonlinear ill-posed problem in low-dose dental cone-beam computed tomography](http://arxiv.org/abs/2303.01678v1)|2023-03-03 02:46:15+00:00|03-03-2023 248 | Tianyi Zhang|[DeepSeer: Interactive RNN Explanation and Debugging via State Abstraction](http://arxiv.org/abs/2303.01576v1)|2023-03-02 21:08:17+00:00|02-03-2023 249 | Yongyi Mao|[Over-training with Mixup May Hurt Generalization](http://arxiv.org/abs/2303.01475v1)|2023-03-02 18:37:34+00:00|02-03-2023 250 | Horst Samulowitz|[A Vision for Semantically Enriched Data Science](http://arxiv.org/abs/2303.01378v1)|2023-03-02 16:03:12+00:00|02-03-2023 251 | Ajitha Rajan|[Explanations for Automatic Speech Recognition](http://arxiv.org/abs/2302.14062v1)|2023-02-27 11:09:19+00:00|27-02-2023 252 | Ramayya Krishnan|[Changes in Commuter Behavior from COVID-19 Lockdowns in the Atlanta Metropolitan Area](http://arxiv.org/abs/2302.13512v1)|2023-02-27 04:24:13+00:00|27-02-2023 253 | 254 | ## 28-02-2023 255 | 256 | main_author|title|update_date|publish_date 257 | ---|---|---|--- 258 | Marzyeh Ghassemi|[Change is Hard: A Closer Look at Subpopulation Shift](http://arxiv.org/abs/2302.12254v1)|2023-02-23 18:59:56+00:00|23-02-2023 259 | Adriano Koshiyama|[Local and Global Explainability Metrics for Machine Learning Predictions](http://arxiv.org/abs/2302.12094v1)|2023-02-23 15:28:36+00:00|23-02-2023 260 | Jürgen Beyerer|[Effects of Architectures on Continual Semantic Segmentation](http://arxiv.org/abs/2302.10718v1)|2023-02-21 15:12:01+00:00|21-02-2023 261 | Katrien Verbert|[Directive Explanations for Monitoring the Risk of Diabetes Onset: Introducing Directive Data-Centric Explanations and Combinations to Support What-If Explorations](http://arxiv.org/abs/2302.10671v1)|2023-02-21 13:40:16+00:00|21-02-2023 262 | Kayhan Batmanghelich|[Route, Interpret, Repeat: Blurring the Line Between Post hoc Explainability and Interpretable Models](http://arxiv.org/abs/2302.10289v1)|2023-02-20 20:25:41+00:00|20-02-2023 263 | Lun Wang|[Why Is Public Pretraining Necessary for Private Model Training?](http://arxiv.org/abs/2302.09483v1)|2023-02-19 05:32:20+00:00|19-02-2023 264 | Jianshu Chen|[Learning Language Representations with Logical Inductive Bias](http://arxiv.org/abs/2302.09458v1)|2023-02-19 02:21:32+00:00|19-02-2023 265 | 266 | ## 21-02-2023 267 | 268 | main_author|title|update_date|publish_date 269 | ---|---|---|--- 270 | Elvio G. Amparore|[Streamlining models with explanations in the learning loop](http://arxiv.org/abs/2302.07760v1)|2023-02-15 16:08:32+00:00|15-02-2023 271 | Antonio Torralba|[ConceptFusion: Open-set Multimodal 3D Mapping](http://arxiv.org/abs/2302.07241v2)|2023-02-15 01:49:09+00:00|14-02-2023 272 | Luis Galárraga|[Effects of Locality and Rule Language on Explanations for Knowledge Graph Embeddings](http://arxiv.org/abs/2302.06967v1)|2023-02-14 10:50:36+00:00|14-02-2023 273 | Yun Fu|[Towards Explainable Visual Anomaly Detection](http://arxiv.org/abs/2302.06670v1)|2023-02-13 20:17:41+00:00|13-02-2023 274 | Lucas Dixon|[Gradient-Based Automated Iterative Recovery for Parameter-Efficient Tuning](http://arxiv.org/abs/2302.06598v1)|2023-02-13 18:54:58+00:00|13-02-2023 275 | Akiko Aizawa|[Analyzing the Effectiveness of the Underlying Reasoning Tasks in Multi-hop Question Answering](http://arxiv.org/abs/2302.05963v1)|2023-02-12 17:32:55+00:00|12-02-2023 276 | Daniel Schwalbe-Koda|[Data efficiency and extrapolation trends in neural network interatomic potentials](http://arxiv.org/abs/2302.05823v1)|2023-02-12 00:34:05+00:00|12-02-2023 277 | Gabriel Moyà-Alcover|[A novel approach to generate datasets with XAI ground truth to evaluate image models](http://arxiv.org/abs/2302.05624v1)|2023-02-11 08:20:17+00:00|11-02-2023 278 | 279 | ## 14-02-2023 280 | 281 | main_author|title|update_date|publish_date 282 | ---|---|---|--- 283 | Steven Maere|[The out-of-sample $R^2$: estimation and inference](http://arxiv.org/abs/2302.05131v1)|2023-02-10 09:29:57+00:00|10-02-2023 284 | Falk Lieder|[What are the mechanisms underlying metacognitive learning?](http://arxiv.org/abs/2302.04840v1)|2023-02-09 18:49:10+00:00|09-02-2023 285 | Chunyang Chen|[Training-free Lexical Backdoor Attacks on Language Models](http://arxiv.org/abs/2302.04116v1)|2023-02-08 15:18:51+00:00|08-02-2023 286 | Gopal Gupta|[Reliable Natural Language Understanding with Large Language Models and Answer Set Programming](http://arxiv.org/abs/2302.03780v2)|2023-02-09 21:06:26+00:00|07-02-2023 287 | My T. Thai|[LAVA: Granular Neuron-Level Explainable AI for Alzheimer's Disease Assessment from Fundus Images](http://arxiv.org/abs/2302.03008v1)|2023-02-06 18:43:10+00:00|06-02-2023 288 | Dacheng Tao|[Neural Collapse Inspired Feature-Classifier Alignment for Few-Shot Class Incremental Learning](http://arxiv.org/abs/2302.03004v1)|2023-02-06 18:39:40+00:00|06-02-2023 289 | Manish Narwaria|[Explainable Machine Learning: The Importance of a System-Centric Perspective](http://arxiv.org/abs/2302.02347v1)|2023-02-05 09:22:00+00:00|05-02-2023 290 | Erman Ayday|[AUTOLYCUS: Exploiting Explainable AI (XAI) for Model Extraction Attacks against Decision Tree Models](http://arxiv.org/abs/2302.02162v1)|2023-02-04 13:23:39+00:00|04-02-2023 291 | 292 | ## 07-02-2023 293 | 294 | main_author|title|update_date|publish_date 295 | ---|---|---|--- 296 | Masao Yasui|[Example-Based Explainable AI and its Application for Remote Sensing Image Classification](http://arxiv.org/abs/2302.01526v1)|2023-02-03 03:48:43+00:00|03-02-2023 297 | Zhouhan Lin|[Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing](http://arxiv.org/abs/2302.01524v1)|2023-02-03 03:38:50+00:00|03-02-2023 298 | Adam Chew|[Diagrammatization: Rationalizing with diagrammatic AI explanations for abductive reasoning on hypotheses](http://arxiv.org/abs/2302.01241v1)|2023-02-02 17:23:28+00:00|02-02-2023 299 | Meetiksha Sorgile|[LesionAid: Vision Transformers-based Skin Lesion Generation and Classification](http://arxiv.org/abs/2302.01104v1)|2023-02-02 13:52:54+00:00|02-02-2023 300 | Jingjing Liu|[ADAPT: Action-aware Driving Caption Transformer](http://arxiv.org/abs/2302.00673v1)|2023-02-01 18:59:19+00:00|01-02-2023 301 | Shahram Rahimi|[TwinExplainer: Explaining Predictions of an Automotive Digital Twin](http://arxiv.org/abs/2302.00152v1)|2023-02-01 00:11:18+00:00|01-02-2023 302 | Wenhui Shi|[BALANCE: Bayesian Linear Attribution for Root Cause Localization](http://arxiv.org/abs/2301.13572v1)|2023-01-31 11:49:26+00:00|31-01-2023 303 | Lionel Briand|[DNN Explanation for Safety Analysis: an Empirical Evaluation of Clustering-based Approaches](http://arxiv.org/abs/2301.13506v1)|2023-01-31 09:46:37+00:00|31-01-2023 304 | Omran Ayoub|[ChatGPT or Human? Detect and Explain. Explaining Decisions of Machine Learning Model for Detecting Short ChatGPT-generated Text](http://arxiv.org/abs/2301.13852v1)|2023-01-30 08:06:08+00:00|30-01-2023 305 | 306 | ## 31-01-2023 307 | 308 | main_author|title|update_date|publish_date 309 | ---|---|---|--- 310 | Yongfeng Zhang|[ExplainableFold: Understanding AlphaFold Prediction with Explainable AI](http://arxiv.org/abs/2301.11765v1)|2023-01-27 15:06:03+00:00|27-01-2023 311 | Bonnie J Dorr|[NLP as a Lens for Causal Analysis and Perception Mining to Infer Mental Health on Social Media](http://arxiv.org/abs/2301.11004v2)|2023-01-29 15:02:54+00:00|26-01-2023 312 | Arlindo L. Oliveira|[Connecting metrics for shape-texture knowledge in computer vision](http://arxiv.org/abs/2301.10608v1)|2023-01-25 14:37:42+00:00|25-01-2023 313 | Thibaut Vidal|[Explainable Data-Driven Optimization: From Context to Decision and Back Again](http://arxiv.org/abs/2301.10074v1)|2023-01-24 15:25:16+00:00|24-01-2023 314 | Kevin Fu|[Side Eye: Characterizing the Limits of POV Acoustic Eavesdropping from Smartphone Cameras with Rolling Shutters and Movable Lenses](http://arxiv.org/abs/2301.10056v2)|2023-01-26 20:11:27+00:00|24-01-2023 315 | George A. Vouros|[Explainable Deep Reinforcement Learning: State of the Art and Challenges](http://arxiv.org/abs/2301.09937v1)|2023-01-24 11:41:25+00:00|24-01-2023 316 | Chenhao Tan|[Selective Explanations: Leveraging Human Input to Align Explainable AI](http://arxiv.org/abs/2301.09656v1)|2023-01-23 19:00:02+00:00|23-01-2023 317 | Pascal Hitzler|[Explaining Deep Learning Hidden Neuron Activations using Concept Induction](http://arxiv.org/abs/2301.09611v1)|2023-01-23 18:14:32+00:00|23-01-2023 318 | Francesca Toni|[SpArX: Sparse Argumentative Explanations for Neural Networks](http://arxiv.org/abs/2301.09559v1)|2023-01-23 17:20:25+00:00|23-01-2023 319 | Brett Mullins|[The Shape of Explanations: A Topological Account of Rule-Based Explanations in Machine Learning](http://arxiv.org/abs/2301.09042v1)|2023-01-22 02:58:00+00:00|22-01-2023 320 | Shakeeb Murtaza|[Counterfactual Explanation and Instance-Generation using Cycle-Consistent Generative Adversarial Networks](http://arxiv.org/abs/2301.08939v1)|2023-01-21 11:14:34+00:00|21-01-2023 321 | Feras A. Batarseh|[ExClaim: Explainable Neural Claim Verification Using Rationalization](http://arxiv.org/abs/2301.08914v1)|2023-01-21 08:26:27+00:00|21-01-2023 322 | 323 | ## 24-01-2023 324 | 325 | main_author|title|update_date|publish_date 326 | ---|---|---|--- 327 | Juha Röning|[Feature Relevance Analysis to Explain Concept Drift -- A Case Study in Human Activity Recognition](http://arxiv.org/abs/2301.08453v1)|2023-01-20 07:34:27+00:00|20-01-2023 328 | Luyao Zhang|[Monotonicity for AI ethics and society: An empirical study of the monotonic neural additive model in criminology, education, health care, and finance](http://arxiv.org/abs/2301.07060v1)|2023-01-17 18:21:31+00:00|17-01-2023 329 | Chan Yeob Yeun|[Explainable Data Poison Attacks on Human Emotion Evaluation Systems based on EEG Signals](http://arxiv.org/abs/2301.06923v1)|2023-01-17 14:44:46+00:00|17-01-2023 330 | Eugenio Di Sciascio|[MAFUS: a Framework to predict mortality risk in MAFLD subjects](http://arxiv.org/abs/2301.06908v1)|2023-01-17 14:19:51+00:00|17-01-2023 331 | Syed B. Alam|[Explainable, Interpretable & Trustworthy AI for Intelligent Digital Twin: Case Study on Remaining Useful Life](http://arxiv.org/abs/2301.06676v1)|2023-01-17 03:17:07+00:00|17-01-2023 332 | 333 | ## 17-01-2023 334 | 335 | main_author|title|update_date|publish_date 336 | ---|---|---|--- 337 | Yun Fu|[Why is the State of Neural Network Pruning so Confusing? On the Fairness, Comparison Setup, and Trainability in Network Pruning](http://arxiv.org/abs/2301.05219v1)|2023-01-12 18:58:33+00:00|12-01-2023 338 | Kazuya Takeda|[Predictive World Models from Real-World Partial Observations](http://arxiv.org/abs/2301.04783v1)|2023-01-12 02:07:26+00:00|12-01-2023 339 | Joshua B. Tenenbaum|[3D Shape Perception Integrates Intuitive Physics and Analysis-by-Synthesis](http://arxiv.org/abs/2301.03711v1)|2023-01-09 23:11:41+00:00|09-01-2023 340 | Suhang Wang|[Faithful and Consistent Graph Neural Network Explanations with Rationale Alignment](http://arxiv.org/abs/2301.02791v1)|2023-01-07 06:33:35+00:00|07-01-2023 341 | 342 | ## 10-01-2023 343 | 344 | main_author|title|update_date|publish_date 345 | ---|---|---|--- 346 | Kai Liu|[Deep Biological Pathway Informed Pathology-Genomic Multimodal Survival Prediction](http://arxiv.org/abs/2301.02383v1)|2023-01-06 05:24:41+00:00|06-01-2023 347 | Lizhen Cui|[Multi-Aspect Explainable Inductive Relation Prediction by Sentence Transformer](http://arxiv.org/abs/2301.01664v1)|2023-01-04 15:33:49+00:00|04-01-2023 348 | Nanne van Noord|[Hierarchical Explanations for Video Action Recognition](http://arxiv.org/abs/2301.00436v2)|2023-01-04 23:32:49+00:00|01-01-2023 349 | 350 | ## 03-01-2023 351 | 352 | main_author|title|update_date|publish_date 353 | ---|---|---|--- 354 | Daniel Sonntag|[DRG-Net: Interactive Joint Learning of Multi-lesion Segmentation and Classification for Diabetic Retinopathy Grading](http://arxiv.org/abs/2212.14615v1)|2022-12-30 09:59:17+00:00|30-12-2022 355 | Maunendra Sankar Desarkar|[ComplAI: Theory of A Unified Framework for Multi-factor Assessment of Black-Box Supervised Machine Learning Models](http://arxiv.org/abs/2212.14599v1)|2022-12-30 08:48:19+00:00|30-12-2022 356 | Zhijie Lin|[Unsupervised Representation Learning from Pre-trained Diffusion Probabilistic Models](http://arxiv.org/abs/2212.12990v2)|2023-01-01 06:01:58+00:00|26-12-2022 357 | Stefan Decker|[Explainable AI for Bioinformatics: Methods, Tools, and Applications](http://arxiv.org/abs/2212.13261v1)|2022-12-25 21:00:36+00:00|25-12-2022 358 | 359 | ## 27-12-2022 360 | 361 | main_author|title|update_date|publish_date 362 | ---|---|---|--- 363 | Annette ten Teije|[A-NeSI: A Scalable Approximate Method for Probabilistic Neurosymbolic Inference](http://arxiv.org/abs/2212.12393v1)|2022-12-23 15:24:53+00:00|23-12-2022 364 | Luoyu Chen|[Depth Estimation maps of lidar and stereo images](http://arxiv.org/abs/2212.11741v1)|2022-12-22 14:32:55+00:00|22-12-2022 365 | Yasushi Okuno|[GraphIX: Graph-based In silico XAI(explainable artificial intelligence) for drug repositioning from biopharmaceutical network](http://arxiv.org/abs/2212.10788v1)|2022-12-21 06:17:45+00:00|21-12-2022 366 | Minlie Huang|[MoralDial: A Framework to Train and Evaluate Moral Dialogue Systems via Constructing Moral Discussions](http://arxiv.org/abs/2212.10720v1)|2022-12-21 02:21:37+00:00|21-12-2022 367 | Kevin Chen-Chuan Chang|[DimonGen: Diversified Generative Commonsense Reasoning for Explaining Concept Relationships](http://arxiv.org/abs/2212.10545v1)|2022-12-20 18:50:29+00:00|20-12-2022 368 | Jean Honorio|[Distributional Robustness Bounds Generalization Errors](http://arxiv.org/abs/2212.09962v1)|2022-12-20 02:30:13+00:00|20-12-2022 369 | Xiang Ren|[KNIFE: Knowledge Distillation with Free-Text Rationales](http://arxiv.org/abs/2212.09721v1)|2022-12-19 18:49:09+00:00|19-12-2022 370 | Milad Lankarany|[Uncovering the Origins of Instability in Dynamical Systems: How Attention Mechanism Can Help?](http://arxiv.org/abs/2212.09641v1)|2022-12-19 17:16:41+00:00|19-12-2022 371 | Jun Zhao|[Large Language Models are reasoners with Self-Verification](http://arxiv.org/abs/2212.09561v1)|2022-12-19 15:51:52+00:00|19-12-2022 372 | Ikuro Sato|[Fixed-Weight Difference Target Propagation](http://arxiv.org/abs/2212.10352v1)|2022-12-19 13:34:36+00:00|19-12-2022 373 | Tanja Käser|[Trusting the Explainers: Teacher Validation of Explainable Artificial Intelligence for Course Design](http://arxiv.org/abs/2212.08955v2)|2022-12-26 02:32:58+00:00|17-12-2022 374 | Jian-Guang Lou|[Know What I don't Know: Handling Ambiguous and Unanswerable Questions for Text-to-SQL](http://arxiv.org/abs/2212.08902v1)|2022-12-17 15:32:00+00:00|17-12-2022 375 | Betul Acunas|[Context-dependent Explainability and Contestability for Trustworthy Medical Artificial Intelligence: Misclassification Identification of Morbidity Recognition Models in Preterm Infants](http://arxiv.org/abs/2212.08821v1)|2022-12-17 07:59:09+00:00|17-12-2022 376 | D. Petkovic|"[It is not ""accuracy vs. explainability"" -- we need both for trustworthy AI systems](http://arxiv.org/abs/2212.11136v2)"|2022-12-23 22:55:33+00:00|16-12-2022 377 | 378 | ## 20-12-2022 379 | 380 | main_author|title|update_date|publish_date 381 | ---|---|---|--- 382 | Erik Learned-Miller|[EVAL: Explainable Video Anomaly Localization](http://arxiv.org/abs/2212.07900v1)|2022-12-15 15:35:25+00:00|15-12-2022 383 | Nitesh V. Chawla|[Interpretable ML for Imbalanced Data](http://arxiv.org/abs/2212.07743v1)|2022-12-15 11:50:31+00:00|15-12-2022 384 | Jared Kaplan|[Constitutional AI: Harmlessness from AI Feedback](http://arxiv.org/abs/2212.08073v1)|2022-12-15 06:19:23+00:00|15-12-2022 385 | Ghassan AlRegib|[Explainable Machine Learning for Hydrocarbon Prospect Risking](http://arxiv.org/abs/2212.07563v1)|2022-12-15 00:38:14+00:00|15-12-2022 386 | Abraham J. Fetterman|"[Despite ""super-human"" performance, current LLMs are unsuited for decisions about ethics and safety](http://arxiv.org/abs/2212.06295v1)"|2022-12-13 00:29:45+00:00|13-12-2022 387 | Alain Mermoud|[Robust and Explainable Identification of Logical Fallacies in Natural Language Arguments](http://arxiv.org/abs/2212.07425v1)|2022-12-12 20:27:17+00:00|12-12-2022 388 | Yong Gao|[GWRBoost:A geographically weighted gradient boosting method for explainable quantification of spatially-varying relationships](http://arxiv.org/abs/2212.05814v2)|2022-12-15 06:02:33+00:00|12-12-2022 389 | Joris Vankerschaver|[Utilizing Mutations to Evaluate Interpretability of Neural Networks on Genomic Data](http://arxiv.org/abs/2212.06151v1)|2022-12-12 07:12:56+00:00|12-12-2022 390 | Riccardo Tommasini|[Multimodal and Explainable Internet Meme Classification](http://arxiv.org/abs/2212.05612v1)|2022-12-11 21:52:21+00:00|11-12-2022 391 | Riccardo Guidotti|[CALIME: Causality-Aware Local Interpretable Model-Agnostic Explanations](http://arxiv.org/abs/2212.05256v1)|2022-12-10 10:12:27+00:00|10-12-2022 392 | My T. Thai|[XRand: Differentially Private Defense against Explanation-Guided Attacks](http://arxiv.org/abs/2212.04454v3)|2022-12-14 18:03:04+00:00|08-12-2022 393 | Liang Zhao|[Going Beyond XAI: A Systematic Survey for Explanation-Guided Learning](http://arxiv.org/abs/2212.03954v1)|2022-12-07 20:59:59+00:00|07-12-2022 394 | Cunqing Ma|[Learning to Select Prototypical Parts for Interpretable Sequential Data Modeling](http://arxiv.org/abs/2212.03396v1)|2022-12-07 01:42:47+00:00|07-12-2022 395 | Hiroyuki Abe|[Achieving Transparency in Distributed Machine Learning with Explainable Data Collaboration](http://arxiv.org/abs/2212.03373v1)|2022-12-06 23:53:41+00:00|06-12-2022 396 | Pierre-Alexandre Mattei|[Explainability as statistical inference](http://arxiv.org/abs/2212.03131v1)|2022-12-06 16:55:10+00:00|06-12-2022 397 | Branka Hadji Misheva|[A Time Series Approach to Explainability for Neural Nets with Applications to Risk-Management and Fraud Detection](http://arxiv.org/abs/2212.02906v1)|2022-12-06 12:04:01+00:00|06-12-2022 398 | Michael Schmitt|[MapInWild: A Remote Sensing Dataset to Address the Question What Makes Nature Wild](http://arxiv.org/abs/2212.02265v1)|2022-12-05 13:45:06+00:00|05-12-2022 399 | Ping Li|[Rethinking the Structure of Stochastic Gradients: Empirical and Statistical Evidence](http://arxiv.org/abs/2212.02083v1)|2022-12-05 07:55:22+00:00|05-12-2022 400 | Defeng Sun|[Beyond ADMM: A Unified Client-variance-reduced Adaptive Federated Learning Framework](http://arxiv.org/abs/2212.01519v1)|2022-12-03 03:27:51+00:00|03-12-2022 401 | 402 | ## 13-12-2022 403 | 404 | main_author|title|update_date|publish_date 405 | ---|---|---|--- 406 | Deyu Zhou|[Exploring Faithful Rationale for Multi-hop Fact Verification via Salience-Aware Graph Learning](http://arxiv.org/abs/2212.01060v1)|2022-12-02 09:54:05+00:00|02-12-2022 407 | Marcos Ortega|[Weakly-supervised detection of AMD-related lesions in color fundus images using explainable deep learning](http://arxiv.org/abs/2212.00565v2)|2022-12-04 15:04:31+00:00|01-12-2022 408 | Sebastian Lapuschkin|[Optimizing Explanations by Network Canonization and Hyperparameter Search](http://arxiv.org/abs/2211.17174v1)|2022-11-30 17:17:55+00:00|30-11-2022 409 | Ashkan Ertefaie|[Relative Sparsity for Medical Decision Problems](http://arxiv.org/abs/2211.16566v1)|2022-11-29 20:00:11+00:00|29-11-2022 410 | Siyu Xia|[Unsupervised Visual Defect Detection with Score-Based Generative Model](http://arxiv.org/abs/2211.16092v1)|2022-11-29 11:06:29+00:00|29-11-2022 411 | Aidong Zhang|[Understanding and Enhancing Robustness of Concept-based Models](http://arxiv.org/abs/2211.16080v1)|2022-11-29 10:43:51+00:00|29-11-2022 412 | Baochang Zhang|[Rethinking the Number of Shots in Robust Model-Agnostic Meta-Learning](http://arxiv.org/abs/2211.15180v1)|2022-11-28 09:47:13+00:00|28-11-2022 413 | Mengjie Zhang|[Explaining Deep Convolutional Neural Networks for Image Classification by Evolving Local Interpretable Model-agnostic Explanations](http://arxiv.org/abs/2211.15143v1)|2022-11-28 08:56:00+00:00|28-11-2022 414 | Arjun Seshadri|[RecXplainer: Post-Hoc Attribute-Based Explanations for Recommender Systems](http://arxiv.org/abs/2211.14935v1)|2022-11-27 21:00:31+00:00|27-11-2022 415 | Moshe Sipper|[Foiling Explanations in Deep Neural Networks](http://arxiv.org/abs/2211.14860v1)|2022-11-27 15:29:39+00:00|27-11-2022 416 | João Paulo Teixeira|[Interpretability Analysis of Deep Models for COVID-19 Detection](http://arxiv.org/abs/2211.14372v1)|2022-11-25 20:56:23+00:00|25-11-2022 417 | H. Vincent Poor|[Less Data, More Knowledge: Building Next Generation Semantic Communication Networks](http://arxiv.org/abs/2211.14343v1)|2022-11-25 19:03:25+00:00|25-11-2022 418 | Shaurya Jain|[Testing the effectiveness of saliency-based explainability in NLP using randomized survey-based experiments](http://arxiv.org/abs/2211.15351v1)|2022-11-25 08:49:01+00:00|25-11-2022 419 | Patrick Mikalef|[Explainable Artificial Intelligence (XAI) from a user perspective- A synthesis of prior literature and problematizing avenues for future research](http://arxiv.org/abs/2211.15343v1)|2022-11-24 20:15:59+00:00|24-11-2022 420 | Tim Räz|[ML Interpretability: Simple Isn't Easy](http://arxiv.org/abs/2211.13617v1)|2022-11-24 14:07:02+00:00|24-11-2022 421 | Benjamin Doerr|[Runtime Analysis for the NSGA-II: Proving, Quantifying, and Explaining the Inefficiency For Three or More Objectives](http://arxiv.org/abs/2211.13084v1)|2022-11-23 16:15:26+00:00|23-11-2022 422 | Pascal Friederich|[MEGAN: Multi-Explanation Graph Attention Network](http://arxiv.org/abs/2211.13236v1)|2022-11-23 16:10:13+00:00|23-11-2022 423 | Richard E. Turner|[Adversarial Attacks are a Surprisingly Strong Baseline for Poisoning Few-Shot Meta-Learners](http://arxiv.org/abs/2211.12990v1)|2022-11-23 14:55:44+00:00|23-11-2022 424 | Karsten Roscher|[Towards Human-Interpretable Prototypes for Visual Assessment of Image Classification Models](http://arxiv.org/abs/2211.12173v1)|2022-11-22 11:01:22+00:00|22-11-2022 425 | Weilin Meng|[Explainability of Traditional and Deep Learning Models on Longitudinal Healthcare Records](http://arxiv.org/abs/2211.12002v1)|2022-11-22 04:39:17+00:00|22-11-2022 426 | Pascal Van Hentenryck|[Fairness Increases Adversarial Vulnerability](http://arxiv.org/abs/2211.11835v2)|2022-11-23 01:46:22+00:00|21-11-2022 427 | Francesca Toni|[Explaining Random Forests using Bipolar Argumentation and Markov Networks (Technical Report)](http://arxiv.org/abs/2211.11699v1)|2022-11-21 18:20:50+00:00|21-11-2022 428 | Lingpeng Kong|[Unsupervised Explanation Generation via Correct Instantiations](http://arxiv.org/abs/2211.11160v1)|2022-11-21 03:10:24+00:00|21-11-2022 429 | Laveti Ramesh Naidu|[Explainable Artificial Intelligence and Causal Inference based ATM Fraud Detection](http://arxiv.org/abs/2211.10595v1)|2022-11-19 06:01:08+00:00|19-11-2022 430 | 431 | ## 06-12-2022 432 | 433 | main_author|title|update_date|publish_date 434 | ---|---|---|--- 435 | Deyu Zhou|[Exploring Faithful Rationale for Multi-hop Fact Verification via Salience-Aware Graph Learning](http://arxiv.org/abs/2212.01060v1)|2022-12-02 09:54:05+00:00|02-12-2022 436 | Marcos Ortega|[Weakly-supervised detection of AMD-related lesions in color fundus images using explainable deep learning](http://arxiv.org/abs/2212.00565v2)|2022-12-04 15:04:31+00:00|01-12-2022 437 | Sebastian Lapuschkin|[Optimizing Explanations by Network Canonization and Hyperparameter Search](http://arxiv.org/abs/2211.17174v1)|2022-11-30 17:17:55+00:00|30-11-2022 438 | Ashkan Ertefaie|[Relative Sparsity for Medical Decision Problems](http://arxiv.org/abs/2211.16566v1)|2022-11-29 20:00:11+00:00|29-11-2022 439 | Siyu Xia|[Unsupervised Visual Defect Detection with Score-Based Generative Model](http://arxiv.org/abs/2211.16092v1)|2022-11-29 11:06:29+00:00|29-11-2022 440 | Aidong Zhang|[Understanding and Enhancing Robustness of Concept-based Models](http://arxiv.org/abs/2211.16080v1)|2022-11-29 10:43:51+00:00|29-11-2022 441 | Baochang Zhang|[Rethinking the Number of Shots in Robust Model-Agnostic Meta-Learning](http://arxiv.org/abs/2211.15180v1)|2022-11-28 09:47:13+00:00|28-11-2022 442 | Mengjie Zhang|[Explaining Deep Convolutional Neural Networks for Image Classification by Evolving Local Interpretable Model-agnostic Explanations](http://arxiv.org/abs/2211.15143v1)|2022-11-28 08:56:00+00:00|28-11-2022 443 | Arjun Seshadri|[RecXplainer: Post-Hoc Attribute-Based Explanations for Recommender Systems](http://arxiv.org/abs/2211.14935v1)|2022-11-27 21:00:31+00:00|27-11-2022 444 | Moshe Sipper|[Foiling Explanations in Deep Neural Networks](http://arxiv.org/abs/2211.14860v1)|2022-11-27 15:29:39+00:00|27-11-2022 445 | João Paulo Teixeira|[Interpretability Analysis of Deep Models for COVID-19 Detection](http://arxiv.org/abs/2211.14372v1)|2022-11-25 20:56:23+00:00|25-11-2022 446 | H. Vincent Poor|[Less Data, More Knowledge: Building Next Generation Semantic Communication Networks](http://arxiv.org/abs/2211.14343v1)|2022-11-25 19:03:25+00:00|25-11-2022 447 | Shaurya Jain|[Testing the effectiveness of saliency-based explainability in NLP using randomized survey-based experiments](http://arxiv.org/abs/2211.15351v1)|2022-11-25 08:49:01+00:00|25-11-2022 448 | Patrick Mikalef|[Explainable Artificial Intelligence (XAI) from a user perspective- A synthesis of prior literature and problematizing avenues for future research](http://arxiv.org/abs/2211.15343v1)|2022-11-24 20:15:59+00:00|24-11-2022 449 | Tim Räz|[ML Interpretability: Simple Isn't Easy](http://arxiv.org/abs/2211.13617v1)|2022-11-24 14:07:02+00:00|24-11-2022 450 | Benjamin Doerr|[Runtime Analysis for the NSGA-II: Proving, Quantifying, and Explaining the Inefficiency For Three or More Objectives](http://arxiv.org/abs/2211.13084v1)|2022-11-23 16:15:26+00:00|23-11-2022 451 | Pascal Friederich|[MEGAN: Multi-Explanation Graph Attention Network](http://arxiv.org/abs/2211.13236v1)|2022-11-23 16:10:13+00:00|23-11-2022 452 | Richard E. Turner|[Adversarial Attacks are a Surprisingly Strong Baseline for Poisoning Few-Shot Meta-Learners](http://arxiv.org/abs/2211.12990v1)|2022-11-23 14:55:44+00:00|23-11-2022 453 | Karsten Roscher|[Towards Human-Interpretable Prototypes for Visual Assessment of Image Classification Models](http://arxiv.org/abs/2211.12173v1)|2022-11-22 11:01:22+00:00|22-11-2022 454 | Weilin Meng|[Explainability of Traditional and Deep Learning Models on Longitudinal Healthcare Records](http://arxiv.org/abs/2211.12002v1)|2022-11-22 04:39:17+00:00|22-11-2022 455 | Pascal Van Hentenryck|[Fairness Increases Adversarial Vulnerability](http://arxiv.org/abs/2211.11835v2)|2022-11-23 01:46:22+00:00|21-11-2022 456 | Francesca Toni|[Explaining Random Forests using Bipolar Argumentation and Markov Networks (Technical Report)](http://arxiv.org/abs/2211.11699v1)|2022-11-21 18:20:50+00:00|21-11-2022 457 | Lingpeng Kong|[Unsupervised Explanation Generation via Correct Instantiations](http://arxiv.org/abs/2211.11160v1)|2022-11-21 03:10:24+00:00|21-11-2022 458 | Laveti Ramesh Naidu|[Explainable Artificial Intelligence and Causal Inference based ATM Fraud Detection](http://arxiv.org/abs/2211.10595v1)|2022-11-19 06:01:08+00:00|19-11-2022 459 | 460 | ## 29-11-2022 461 | 462 | main_author|title|update_date|publish_date 463 | ---|---|---|--- 464 | Alexander Wong|[SolderNet: Towards Trustworthy Visual Inspection of Solder Joints in Electronics Manufacturing Using Explainable Artificial Intelligence](http://arxiv.org/abs/2211.10274v1)|2022-11-18 15:02:59+00:00|18-11-2022 465 | Hitoshi Iyatomi|[Feedback is Needed for Retakes: An Explainable Poor Image Notification Framework for the Visually Impaired](http://arxiv.org/abs/2211.09427v1)|2022-11-17 09:22:28+00:00|17-11-2022 466 | Bing Yin|[FolkScope: Intention Knowledge Graph Construction for Discovering E-commerce Commonsense](http://arxiv.org/abs/2211.08316v1)|2022-11-15 17:20:40+00:00|15-11-2022 467 | Katia Sycara|[Explainable Action Advising for Multi-Agent Reinforcement Learning](http://arxiv.org/abs/2211.07882v1)|2022-11-15 04:15:03+00:00|15-11-2022 468 | Ryota Kanai|[Logical Tasks for Measuring Extrapolation and Rule Comprehension](http://arxiv.org/abs/2211.07727v1)|2022-11-14 19:55:54+00:00|14-11-2022 469 | Yang Yu|[Does Debiasing Inevitably Degrade the Model Performance](http://arxiv.org/abs/2211.07350v1)|2022-11-14 13:46:13+00:00|14-11-2022 470 | Dhananjay Kalbande|[A Pipeline for Business Intelligence and Data-Driven Root Cause Analysis on Categorical Data](http://arxiv.org/abs/2211.06717v1)|2022-11-12 18:12:10+00:00|12-11-2022 471 | Mingli Song|[A Survey on Explainable Reinforcement Learning: Concepts, Algorithms, Challenges](http://arxiv.org/abs/2211.06665v2)|2022-11-15 07:49:44+00:00|12-11-2022 472 | 473 | ## 22-11-2022 474 | 475 | main_author|title|update_date|publish_date 476 | ---|---|---|--- 477 | Alexander Wong|[SolderNet: Towards Trustworthy Visual Inspection of Solder Joints in Electronics Manufacturing Using Explainable Artificial Intelligence](http://arxiv.org/abs/2211.10274v1)|2022-11-18 15:02:59+00:00|18-11-2022 478 | Hitoshi Iyatomi|[Feedback is Needed for Retakes: An Explainable Poor Image Notification Framework for the Visually Impaired](http://arxiv.org/abs/2211.09427v1)|2022-11-17 09:22:28+00:00|17-11-2022 479 | Bing Yin|[FolkScope: Intention Knowledge Graph Construction for Discovering E-commerce Commonsense](http://arxiv.org/abs/2211.08316v1)|2022-11-15 17:20:40+00:00|15-11-2022 480 | Katia Sycara|[Explainable Action Advising for Multi-Agent Reinforcement Learning](http://arxiv.org/abs/2211.07882v1)|2022-11-15 04:15:03+00:00|15-11-2022 481 | Ryota Kanai|[Logical Tasks for Measuring Extrapolation and Rule Comprehension](http://arxiv.org/abs/2211.07727v1)|2022-11-14 19:55:54+00:00|14-11-2022 482 | Yang Yu|[Does Debiasing Inevitably Degrade the Model Performance](http://arxiv.org/abs/2211.07350v1)|2022-11-14 13:46:13+00:00|14-11-2022 483 | Dhananjay Kalbande|[A Pipeline for Business Intelligence and Data-Driven Root Cause Analysis on Categorical Data](http://arxiv.org/abs/2211.06717v1)|2022-11-12 18:12:10+00:00|12-11-2022 484 | Mingli Song|[A Survey on Explainable Reinforcement Learning: Concepts, Algorithms, Challenges](http://arxiv.org/abs/2211.06665v2)|2022-11-15 07:49:44+00:00|12-11-2022 485 | 486 | ## 15-11-2022 487 | 488 | main_author|title|update_date|publish_date 489 | ---|---|---|--- 490 | Sebastian Farquhar|[Understanding Approximation for Bayesian Inference in Neural Networks](http://arxiv.org/abs/2211.06139v1)|2022-11-11 11:31:13+00:00|11-11-2022 491 | Govind Thattai|[Towards Reasoning-Aware Explainable VQA](http://arxiv.org/abs/2211.05190v1)|2022-11-09 20:47:45+00:00|09-11-2022 492 | Pratap Tokekar|[Interpretable Deep Reinforcement Learning for Green Security Games with Real-Time Information](http://arxiv.org/abs/2211.04987v1)|2022-11-09 16:03:45+00:00|09-11-2022 493 | Pepa Atanasova|[Accountable and Explainable Methods for Complex Reasoning over Text](http://arxiv.org/abs/2211.04946v1)|2022-11-09 15:14:52+00:00|09-11-2022 494 | Yan He|[Deep Explainable Learning with Graph Based Data Assessing and Rule Reasoning](http://arxiv.org/abs/2211.04693v2)|2022-11-10 11:41:56+00:00|09-11-2022 495 | Shah Muhammad Hamdi|[Motif-guided Time Series Counterfactual Explanations](http://arxiv.org/abs/2211.04411v2)|2022-11-11 19:41:35+00:00|08-11-2022 496 | Manuela Veloso|[Towards learning to explain with concept bottleneck models: mitigating information leakage](http://arxiv.org/abs/2211.03656v1)|2022-11-07 16:10:36+00:00|07-11-2022 497 | Alpan Raval|[Predicting Treatment Adherence of Tuberculosis Patients at Scale](http://arxiv.org/abs/2211.02943v1)|2022-11-05 17:00:21+00:00|05-11-2022 498 | Leman Akoglu|[Unsupervised Machine Learning for Explainable Medicare Fraud Detection](http://arxiv.org/abs/2211.02927v2)|2022-11-09 15:18:19+00:00|05-11-2022 499 | 500 | ## 08-11-2022 501 | 502 | main_author|title|update_date|publish_date 503 | ---|---|---|--- 504 | Zhaoyang Zhang|[Explainable AI over the Internet of Things (IoT): Overview, State-of-the-Art and Future Directions](http://arxiv.org/abs/2211.01036v2)|2022-11-07 07:06:14+00:00|02-11-2022 505 | Stefan Lessmann|[A Data-driven Case-based Reasoning in Bankruptcy Prediction](http://arxiv.org/abs/2211.00921v1)|2022-11-02 07:10:09+00:00|02-11-2022 506 | Peter Tu|[Understanding the Unforeseen via the Intentional Stance](http://arxiv.org/abs/2211.00478v1)|2022-11-01 14:14:14+00:00|01-11-2022 507 | Sander Beckers|[Backtracking Counterfactuals](http://arxiv.org/abs/2211.00472v1)|2022-11-01 14:07:30+00:00|01-11-2022 508 | Kyung-Ah Sohn|[Why Is It Hate Speech? Masked Rationale Prediction for Explainable Hate Speech Detection](http://arxiv.org/abs/2211.00243v1)|2022-11-01 03:16:36+00:00|01-11-2022 509 | Ashwin Kalyan|[Lila: A Unified Benchmark for Mathematical Reasoning](http://arxiv.org/abs/2210.17517v1)|2022-10-31 17:41:26+00:00|31-10-2022 510 | Nidhi Rastogi|[SoK: Modeling Explainability in Security Monitoring for Trust, Privacy, and Interpretability](http://arxiv.org/abs/2210.17376v1)|2022-10-31 15:01:49+00:00|31-10-2022 511 | Zheng Zhang|[RLET: A Reinforcement Learning Based Approach for Explainable QA with Entailment Trees](http://arxiv.org/abs/2210.17095v1)|2022-10-31 06:45:05+00:00|31-10-2022 512 | Byung-Hak Kim|[Medical Codes Prediction from Clinical Notes: From Human Coders to Machines](http://arxiv.org/abs/2210.16850v1)|2022-10-30 14:24:13+00:00|30-10-2022 513 | Roger Wattenhofer|[Neural Combinatorial Logic Circuit Synthesis from Input-Output Examples](http://arxiv.org/abs/2210.16606v1)|2022-10-29 14:06:42+00:00|29-10-2022 514 | 515 | ## 01-11-2022 516 | 517 | main_author|title|update_date|publish_date 518 | ---|---|---|--- 519 | Varun Ganapathi|[Can Current Explainability Help Provide References in Clinical Notes to Support Humans Annotate Medical Codes?](http://arxiv.org/abs/2210.15882v1)|2022-10-28 04:06:07+00:00|28-10-2022 520 | Nick Sajadi|[Reverse Survival Model (RSM): A Pipeline for Explaining Predictions of Deep Survival Models](http://arxiv.org/abs/2210.15674v1)|2022-10-27 03:39:01+00:00|27-10-2022 521 | Wenchuan Mu|[Similarity between Units of Natural Language: The Transition from Coarse to Fine Estimation](http://arxiv.org/abs/2210.14275v1)|2022-10-25 18:54:32+00:00|25-10-2022 522 | Andreas Geiger|[PlanT: Explainable Planning Transformers via Object-Level Representations](http://arxiv.org/abs/2210.14222v1)|2022-10-25 17:59:46+00:00|25-10-2022 523 | Guy Katz|[Towards Formal Approximated Minimal Explanations of Neural Networks](http://arxiv.org/abs/2210.13915v1)|2022-10-25 11:06:37+00:00|25-10-2022 524 | Vered Shwartz|[VLC-BERT: Visual Question Answering with Contextualized Commonsense Knowledge](http://arxiv.org/abs/2210.13626v1)|2022-10-24 22:01:17+00:00|24-10-2022 525 | Ana Marasović|[Does Self-Rationalization Improve Robustness to Spurious Correlations?](http://arxiv.org/abs/2210.13575v1)|2022-10-24 19:54:57+00:00|24-10-2022 526 | Tatiana Shavrina|[Universal and Independent: Multilingual Probing Framework for Exhaustive Model Interpretation and Evaluation](http://arxiv.org/abs/2210.13236v1)|2022-10-24 13:41:17+00:00|24-10-2022 527 | Xiao Xiang Zhu|[Exploring Self-Attention for Crop-type Classification Explainability](http://arxiv.org/abs/2210.13167v1)|2022-10-24 12:36:40+00:00|24-10-2022 528 | Zheng Zhang|[Self-supervised Amodal Video Object Segmentation](http://arxiv.org/abs/2210.12733v1)|2022-10-23 14:09:35+00:00|23-10-2022 529 | Joyce Chai|[DANLI: Deliberative Agent for Following Natural Language Instructions](http://arxiv.org/abs/2210.12485v1)|2022-10-22 15:57:01+00:00|22-10-2022 530 | 531 | ## 25-10-2022 532 | 533 | main_author|title|update_date|publish_date 534 | ---|---|---|--- 535 | William Yang Wang|[WikiWhy: Answering and Explaining Cause-and-Effect Questions](http://arxiv.org/abs/2210.12152v1)|2022-10-21 17:59:03+00:00|21-10-2022 536 | Benoit Favre|[Do Vision-and-Language Transformers Learn Grounded Predicate-Noun Dependencies?](http://arxiv.org/abs/2210.12079v1)|2022-10-21 16:07:00+00:00|21-10-2022 537 | Ambuj Singh|[Global Counterfactual Explainer for Graph Neural Networks](http://arxiv.org/abs/2210.11695v1)|2022-10-21 02:46:35+00:00|21-10-2022 538 | David Freire-Obregón|[Deep Learning for Diagonal Earlobe Crease Detection](http://arxiv.org/abs/2210.11582v1)|2022-10-20 20:51:48+00:00|20-10-2022 539 | David Chiang|[A Continuum of Generation Tasks for Investigating Length Bias and Degenerate Repetition](http://arxiv.org/abs/2210.10817v1)|2022-10-19 18:09:51+00:00|19-10-2022 540 | Daniel Berleant|[Discovering Limitations of Image Quality Assessments with Noised Deep Learning Image Sets](http://arxiv.org/abs/2210.10249v1)|2022-10-19 02:15:09+00:00|19-10-2022 541 | Jun Zhao|[ReasonChainQA: Text-based Complex Question Answering with Explainable Evidence Chains](http://arxiv.org/abs/2210.08763v1)|2022-10-17 06:07:39+00:00|17-10-2022 542 | Heng Ji|[NormSAGE: Multi-Lingual Multi-Cultural Norm Discovery from Conversations On-the-Fly](http://arxiv.org/abs/2210.08604v1)|2022-10-16 18:30:05+00:00|16-10-2022 543 | Gunjan Saxena|[Explainable Causal Analysis of Mental Health on Social Media Data](http://arxiv.org/abs/2210.08430v1)|2022-10-16 03:34:47+00:00|16-10-2022 544 | Lianghua He|[DProtoNet: Decoupling the inference module and the explanation module enables neural networks to have better accuracy and interpretability](http://arxiv.org/abs/2210.08336v1)|2022-10-15 17:05:55+00:00|15-10-2022 545 | 546 | ## 18-10-2022 547 | 548 | main_author|title|update_date|publish_date 549 | ---|---|---|--- 550 | Ioanna Constantiou|[Machine Learning in Transaction Monitoring: The Prospect of xAI](http://arxiv.org/abs/2210.07648v1)|2022-10-14 08:58:35+00:00|14-10-2022 551 | Meeyoung Cha|[Self-explaining deep models with logic rule reasoning](http://arxiv.org/abs/2210.07024v2)|2022-10-17 08:24:42+00:00|13-10-2022 552 | Mariette Awad|[On the Evaluation of the Plausibility and Faithfulness of Sentiment Analysis Explanations](http://arxiv.org/abs/2210.06916v1)|2022-10-13 11:29:17+00:00|13-10-2022 553 | Xifeng Yan|[Explanations from Large Language Models Make Small Reasoners Better](http://arxiv.org/abs/2210.06726v1)|2022-10-13 04:50:02+00:00|13-10-2022 554 | Vipin Kumar|[Probabilistic Inverse Modeling: An Application in Hydrology](http://arxiv.org/abs/2210.06213v1)|2022-10-12 14:00:37+00:00|12-10-2022 555 | Klaus Pohl|[Explaining Online Reinforcement Learning Decisions of Self-Adaptive Systems](http://arxiv.org/abs/2210.05931v1)|2022-10-12 05:38:27+00:00|12-10-2022 556 | Chongqing Kang|[Improving Sample Efficiency of Deep Learning Models in Electricity Market](http://arxiv.org/abs/2210.05599v1)|2022-10-11 16:35:13+00:00|11-10-2022 557 | Thomas Hartvigsen|[Class-Specific Explainability for Deep Time Series Classifiers](http://arxiv.org/abs/2210.05411v1)|2022-10-11 12:37:15+00:00|11-10-2022 558 | Hans Dieter Schotten|[On Explainability in AI-Solutions: A Cross-Domain Survey](http://arxiv.org/abs/2210.05173v1)|2022-10-11 06:21:47+00:00|11-10-2022 559 | Swabha Swayamdipta|[REV: Information-Theoretic Evaluation of Free-Text Rationales](http://arxiv.org/abs/2210.04982v2)|2022-10-14 21:17:07+00:00|10-10-2022 560 | Mayukha Pal|[Local Interpretable Model Agnostic Shap Explanations for machine learning models](http://arxiv.org/abs/2210.04533v1)|2022-10-10 10:07:27+00:00|10-10-2022 561 | Preslav Nakov|[CrowdChecked: Detecting Previously Fact-Checked Claims in Social Media](http://arxiv.org/abs/2210.04447v1)|2022-10-10 06:05:52+00:00|10-10-2022 562 | 563 | ## 11-10-2022 564 | 565 | main_author|title|update_date|publish_date 566 | ---|---|---|--- 567 | Xujie Si|[Novice Type Error Diagnosis with Natural Language Models](http://arxiv.org/abs/2210.03682v1)|2022-10-07 16:40:53+00:00|07-10-2022 568 | Jinhu Lv|[IDa-Det: An Information Discrepancy-aware Distillation for 1-bit Detectors](http://arxiv.org/abs/2210.03477v1)|2022-10-07 12:04:14+00:00|07-10-2022 569 | MD. Golam Rabiul Alam|[Explainable AI based Glaucoma Detection using Transfer Learning and LIME](http://arxiv.org/abs/2210.03332v1)|2022-10-07 05:36:33+00:00|07-10-2022 570 | Marcus Antonio Viana Duarte|[Fault Diagnosis using eXplainable AI: a Transfer Learning-based Approach for Rotating Machinery exploiting Augmented Synthetic Data](http://arxiv.org/abs/2210.02974v1)|2022-10-06 15:02:35+00:00|06-10-2022 571 | David Mimno|[Honest Students from Untrusted Teachers: Learning an Interpretable Question-Answering Pipeline from a Pretrained Language Model](http://arxiv.org/abs/2210.02498v1)|2022-10-05 18:23:49+00:00|05-10-2022 572 | Suhang Wang|[Towards Prototype-Based Self-Explainable Graph Neural Network](http://arxiv.org/abs/2210.01974v1)|2022-10-05 00:47:42+00:00|05-10-2022 573 | Sergey Tulyakov|[Affection: Learning Affective Explanations for Real-World Visual Data](http://arxiv.org/abs/2210.01946v1)|2022-10-04 22:44:17+00:00|04-10-2022 574 | Ronnie C. O. Alves|[Explanation-by-Example Based on Item Response Theory](http://arxiv.org/abs/2210.01638v1)|2022-10-04 14:36:33+00:00|04-10-2022 575 | Krzysztof Czarnecki|[Interpretable Deep Tracking](http://arxiv.org/abs/2210.01266v1)|2022-10-03 23:15:13+00:00|03-10-2022 576 | Max Tegmark|[Omnigrok: Grokking Beyond Algorithmic Data](http://arxiv.org/abs/2210.01117v1)|2022-10-03 17:58:04+00:00|03-10-2022 577 | Luc Van Gool|[Basic Binary Convolution Unit for Binarized Image Restoration Network](http://arxiv.org/abs/2210.00405v1)|2022-10-02 01:54:40+00:00|02-10-2022 578 | Ethem Alpaydın|[PathFinder: Discovering Decision Pathways in Deep Neural Networks](http://arxiv.org/abs/2210.00319v1)|2022-10-01 16:49:55+00:00|01-10-2022 579 | Jason D. Lee|[Self-Stabilization: The Implicit Bias of Gradient Descent at the Edge of Stability](http://arxiv.org/abs/2209.15594v1)|2022-09-30 17:15:12+00:00|30-09-2022 580 | Alessandro Abate|[Observational Robustness and Invariances in Reinforcement Learning via Lexicographic Objectives](http://arxiv.org/abs/2209.15320v1)|2022-09-30 08:53:18+00:00|30-09-2022 581 | Wonju Lee|[Recipro-CAM: Gradient-free reciprocal class activation map](http://arxiv.org/abs/2209.14074v1)|2022-09-28 13:15:03+00:00|28-09-2022 582 | Michael R. Benjamin|[Towards Explaining Autonomy with Verbalised Decision Tree States](http://arxiv.org/abs/2209.13985v1)|2022-09-28 10:28:01+00:00|28-09-2022 583 | Xingxing Wei|[Translation, Scale and Rotation: Cross-Modal Alignment Meets RGB-Infrared Vehicle Detection](http://arxiv.org/abs/2209.13801v1)|2022-09-28 03:06:18+00:00|28-09-2022 584 | G. Lewis|[Predicting Swarm Equatorial Plasma Bubbles Via Supervised Machine Learning](http://arxiv.org/abs/2209.13482v1)|2022-09-27 15:55:23+00:00|27-09-2022 585 | Dinh Phung|[Learning to Counter: Stochastic Feature-based Learning for Diverse Counterfactual Explanations](http://arxiv.org/abs/2209.13446v1)|2022-09-27 15:09:13+00:00|27-09-2022 586 | Chen Zhang|[Asset Pricing and Deep Learning](http://arxiv.org/abs/2209.12014v1)|2022-09-24 14:18:07+00:00|24-09-2022 587 | 588 | ## 27-09-2022 589 | 590 | main_author|title|update_date|publish_date 591 | ---|---|---|--- 592 | Chris Callison-Burch|[Towards Faithful Model Explanation in NLP: A Survey](http://arxiv.org/abs/2209.11326v1)|2022-09-22 21:40:51+00:00|22-09-2022 593 | Vasileios Mezaris|[Learning Visual Explanations for DCNN-Based Image Classifiers Using an Attention Mechanism](http://arxiv.org/abs/2209.11189v1)|2022-09-22 17:33:18+00:00|22-09-2022 594 | Qing Li|[A Comprehensive Survey on Trustworthy Recommender Systems](http://arxiv.org/abs/2209.10117v1)|2022-09-21 04:34:17+00:00|21-09-2022 595 | Ashwin Kalyan|[Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering](http://arxiv.org/abs/2209.09513v1)|2022-09-20 07:04:24+00:00|20-09-2022 596 | Damian Borth|[RESHAPE: Explaining Accounting Anomalies in Financial Statement Audits by enhancing SHapley Additive exPlanations](http://arxiv.org/abs/2209.09157v1)|2022-09-19 16:23:43+00:00|19-09-2022 597 | Prateek Saxena|[Membership Inference Attacks and Generalization: A Causal Perspective](http://arxiv.org/abs/2209.08615v1)|2022-09-18 17:31:11+00:00|18-09-2022 598 | 599 | ## 20-09-2022 600 | 601 | main_author|title|update_date|publish_date 602 | ---|---|---|--- 603 | Nicolas Szczepanski|[Computing Abductive Explanations for Boosted Trees](http://arxiv.org/abs/2209.07740v1)|2022-09-16 06:53:42+00:00|16-09-2022 604 | Steffen Herbold|[Studying the explanations for the automated prediction of bug and non-bug issues using LIME and SHAP](http://arxiv.org/abs/2209.07623v1)|2022-09-15 21:45:46+00:00|15-09-2022 605 | Dongfang Liu|[Visual Recognition with Deep Nearest Centroids](http://arxiv.org/abs/2209.07383v1)|2022-09-15 15:47:31+00:00|15-09-2022 606 | Han-Wei Shen|[GNNInterpreter: A Probabilistic Generative Model-Level Explanation for Graph Neural Networks](http://arxiv.org/abs/2209.07924v1)|2022-09-15 07:45:35+00:00|15-09-2022 607 | Franca Delmastro|[Explainable AI for clinical and remote health applications: a survey on tabular and time series data](http://arxiv.org/abs/2209.06528v1)|2022-09-14 10:01:29+00:00|14-09-2022 608 | Vito Latora|[Deep Neural Networks as Complex Networks](http://arxiv.org/abs/2209.05488v1)|2022-09-12 16:26:04+00:00|12-09-2022 609 | Weisong Shi|[Understanding Time Variations of DNN Inference in Autonomous Driving](http://arxiv.org/abs/2209.05487v1)|2022-09-12 15:20:45+00:00|12-09-2022 610 | Khaza Anuarul Hoque|[TruVR: Trustworthy Cybersickness Detection using Explainable Machine Learning](http://arxiv.org/abs/2209.05257v1)|2022-09-12 13:55:13+00:00|12-09-2022 611 | Yiran Chen|[Fine-grain Inference on Out-of-Distribution Data with Hierarchical Classification](http://arxiv.org/abs/2209.04493v1)|2022-09-09 18:52:36+00:00|09-09-2022 612 | Chengzhi Zhang|[Does Attention Mechanism Possess the Feature of Human Reading? A Perspective of Sentiment Classification Task](http://arxiv.org/abs/2209.03557v1)|2022-09-08 04:19:48+00:00|08-09-2022 613 | Christin Seifert|[Explaining Machine Learning Models in Natural Conversations: Towards a Conversational XAI Agent](http://arxiv.org/abs/2209.02552v1)|2022-09-06 15:01:06+00:00|06-09-2022 614 | Dmitry Koroteev|[Making the black-box brighter: interpreting machine learning algorithm for forecasting drilling accidents](http://arxiv.org/abs/2209.02256v1)|2022-09-06 07:06:16+00:00|06-09-2022 615 | Jörn Kohlhammer|[Visualization Of Class Activation Maps To Explain AI Classification Of Network Packet Captures](http://arxiv.org/abs/2209.02045v1)|2022-09-05 16:34:43+00:00|05-09-2022 616 | W. J. A. van Heeswijk|[Natural Policy Gradients In Reinforcement Learning Explained](http://arxiv.org/abs/2209.01820v1)|2022-09-05 08:06:29+00:00|05-09-2022 617 | Naser Damer|[Towards Explaining Demographic Bias through the Eyes of Face Recognition Models](http://arxiv.org/abs/2208.13400v1)|2022-08-29 07:23:06+00:00|29-08-2022 618 | Xin Eric Wang|[JARVIS: A Neuro-Symbolic Commonsense Reasoning Framework for Conversational Embodied Agents](http://arxiv.org/abs/2208.13266v3)|2022-09-07 14:43:22+00:00|28-08-2022 619 | Hongjing Xia|[Interpretable (not just posthoc-explainable) medical claims modeling for discharge placement to prevent avoidable all-cause readmissions or death](http://arxiv.org/abs/2208.12814v1)|2022-08-28 06:19:32+00:00|28-08-2022 620 | 621 | ## 13-09-2022 622 | 623 | main_author|title|update_date|publish_date 624 | ---|---|---|--- 625 | Christian W. Omlin|[Symbolic Explanation of Affinity-Based Reinforcement Learning Agents with Markov Models](http://arxiv.org/abs/2208.12627v2)|2022-08-29 06:13:56+00:00|26-08-2022 626 | Lars Holmberg|[Towards Benchmarking Explainable Artificial Intelligence Methods](http://arxiv.org/abs/2208.12120v1)|2022-08-25 14:28:30+00:00|25-08-2022 627 | Luciano Serafini|[Deep Symbolic Learning: Discovering Symbols and Rules from Perceptions](http://arxiv.org/abs/2208.11561v1)|2022-08-24 14:06:55+00:00|24-08-2022 628 | Thorsten Staake|[Augmented cross-selling through explainable AI -- a case from energy retailing](http://arxiv.org/abs/2208.11404v1)|2022-08-24 09:51:52+00:00|24-08-2022 629 | Pietro Lió|[Global Concept-Based Interpretability for Graph Neural Networks via Neuron Analysis](http://arxiv.org/abs/2208.10609v1)|2022-08-22 21:30:55+00:00|22-08-2022 630 | Shah Muhammad Hamdi|[Shapelet-Based Counterfactual Explanations for Multivariate Time Series](http://arxiv.org/abs/2208.10462v1)|2022-08-22 17:33:31+00:00|22-08-2022 631 | Mingli Song|[ProtoPFormer: Concentrating on Prototypical Parts in Vision Transformers for Interpretable Image Recognition](http://arxiv.org/abs/2208.10431v1)|2022-08-22 16:36:32+00:00|22-08-2022 632 | Xuanjing Huang|[Locate Then Ask: Interpretable Stepwise Reasoning for Multi-hop Question Answering](http://arxiv.org/abs/2208.10297v1)|2022-08-22 13:24:25+00:00|22-08-2022 633 | 634 | ## 06-09-2022 635 | 636 | main_author|title|update_date|publish_date 637 | ---|---|---|--- 638 | Christian W. Omlin|[Symbolic Explanation of Affinity-Based Reinforcement Learning Agents with Markov Models](http://arxiv.org/abs/2208.12627v2)|2022-08-29 06:13:56+00:00|26-08-2022 639 | Lars Holmberg|[Towards Benchmarking Explainable Artificial Intelligence Methods](http://arxiv.org/abs/2208.12120v1)|2022-08-25 14:28:30+00:00|25-08-2022 640 | Luciano Serafini|[Deep Symbolic Learning: Discovering Symbols and Rules from Perceptions](http://arxiv.org/abs/2208.11561v1)|2022-08-24 14:06:55+00:00|24-08-2022 641 | Thorsten Staake|[Augmented cross-selling through explainable AI -- a case from energy retailing](http://arxiv.org/abs/2208.11404v1)|2022-08-24 09:51:52+00:00|24-08-2022 642 | Pietro Lió|[Global Concept-Based Interpretability for Graph Neural Networks via Neuron Analysis](http://arxiv.org/abs/2208.10609v1)|2022-08-22 21:30:55+00:00|22-08-2022 643 | Shah Muhammad Hamdi|[Shapelet-Based Counterfactual Explanations for Multivariate Time Series](http://arxiv.org/abs/2208.10462v1)|2022-08-22 17:33:31+00:00|22-08-2022 644 | Mingli Song|[ProtoPFormer: Concentrating on Prototypical Parts in Vision Transformers for Interpretable Image Recognition](http://arxiv.org/abs/2208.10431v1)|2022-08-22 16:36:32+00:00|22-08-2022 645 | Xuanjing Huang|[Locate Then Ask: Interpretable Stepwise Reasoning for Multi-hop Question Answering](http://arxiv.org/abs/2208.10297v1)|2022-08-22 13:24:25+00:00|22-08-2022 646 | 647 | ## 30-08-2022 648 | 649 | main_author|title|update_date|publish_date 650 | ---|---|---|--- 651 | Christian W. Omlin|[Symbolic Explanation of Affinity-Based Reinforcement Learning Agents with Markov Models](http://arxiv.org/abs/2208.12627v2)|2022-08-29 06:13:56+00:00|26-08-2022 652 | Lars Holmberg|[Towards Benchmarking Explainable Artificial Intelligence Methods](http://arxiv.org/abs/2208.12120v1)|2022-08-25 14:28:30+00:00|25-08-2022 653 | Luciano Serafini|[Deep Symbolic Learning: Discovering Symbols and Rules from Perceptions](http://arxiv.org/abs/2208.11561v1)|2022-08-24 14:06:55+00:00|24-08-2022 654 | Thorsten Staake|[Augmented cross-selling through explainable AI -- a case from energy retailing](http://arxiv.org/abs/2208.11404v1)|2022-08-24 09:51:52+00:00|24-08-2022 655 | Pietro Lió|[Global Concept-Based Interpretability for Graph Neural Networks via Neuron Analysis](http://arxiv.org/abs/2208.10609v1)|2022-08-22 21:30:55+00:00|22-08-2022 656 | Shah Muhammad Hamdi|[Shapelet-Based Counterfactual Explanations for Multivariate Time Series](http://arxiv.org/abs/2208.10462v1)|2022-08-22 17:33:31+00:00|22-08-2022 657 | Mingli Song|[ProtoPFormer: Concentrating on Prototypical Parts in Vision Transformers for Interpretable Image Recognition](http://arxiv.org/abs/2208.10431v1)|2022-08-22 16:36:32+00:00|22-08-2022 658 | Xuanjing Huang|[Locate Then Ask: Interpretable Stepwise Reasoning for Multi-hop Question Answering](http://arxiv.org/abs/2208.10297v1)|2022-08-22 13:24:25+00:00|22-08-2022 659 | 660 | ## 23-08-2022 661 | 662 | main_author|title|update_date|publish_date 663 | ---|---|---|--- 664 | Iryna Gurevych|[UKP-SQuARE v2 Explainability and Adversarial Attacks for Trustworthy QA](http://arxiv.org/abs/2208.09316v1)|2022-08-19 13:01:01+00:00|19-08-2022 665 | Guoping Qiu|[Restoration of User Videos Shared on Social Media](http://arxiv.org/abs/2208.08597v1)|2022-08-18 02:28:43+00:00|18-08-2022 666 | Melinda Gervasio|[A Framework for Understanding and Visualizing Strategies of RL Agents](http://arxiv.org/abs/2208.08552v1)|2022-08-17 21:58:19+00:00|17-08-2022 667 | Jian Jiao|[The Counterfactual-Shapley Value: Attributing Change in System Metrics](http://arxiv.org/abs/2208.08399v1)|2022-08-17 16:48:20+00:00|17-08-2022 668 | Chirag Shah|[EGCR: Explanation Generation for Conversational Recommendation](http://arxiv.org/abs/2208.08035v2)|2022-08-18 17:56:44+00:00|17-08-2022 669 | Jie Tang|[Mask and Reason: Pre-Training Knowledge Graph Transformers for Complex Logical Queries](http://arxiv.org/abs/2208.07638v1)|2022-08-16 09:51:26+00:00|16-08-2022 670 | Bei Wang|[The SVD of Convolutional Weights: A CNN Interpretability Framework](http://arxiv.org/abs/2208.06894v1)|2022-08-14 18:23:02+00:00|14-08-2022 671 | Vignesh Subbian|[An Empirical Comparison of Explainable Artificial Intelligence Methods for Clinical Data: A Case Study on Traumatic Brain Injury](http://arxiv.org/abs/2208.06717v1)|2022-08-13 19:44:00+00:00|13-08-2022 672 | 673 | ## 16-08-2022 674 | 675 | main_author|title|update_date|publish_date 676 | ---|---|---|--- 677 | Shalom Lappin|[Assessing the Unitary RNN as an End-to-End Compositional Model of Syntax](http://arxiv.org/abs/2208.05719v1)|2022-08-11 09:30:49+00:00|11-08-2022 678 | Mykel J. Kochenderfer|[EvolveHypergraph: Group-Aware Dynamic Relational Reasoning for Trajectory Prediction](http://arxiv.org/abs/2208.05470v1)|2022-08-10 17:57:10+00:00|10-08-2022 679 | Battista Biggio|[Explaining Machine Learning DGA Detectors from DNS Traffic Data](http://arxiv.org/abs/2208.05285v1)|2022-08-10 11:34:26+00:00|10-08-2022 680 | 681 | ## 09-08-2022 682 | 683 | main_author|title|update_date|publish_date 684 | ---|---|---|--- 685 | Sabah Jassim|[Artificial Image Tampering Distorts Spatial Distribution of Texture Landmarks and Quality Characteristics](http://arxiv.org/abs/2208.02710v1)|2022-08-04 15:13:00+00:00|04-08-2022 686 | Ali Hakan Işık|[Diagnosis of Paratuberculosis in Histopathological Images Based on Explainable Artificial Intelligence and Deep Learning](http://arxiv.org/abs/2208.01674v1)|2022-08-02 18:05:26+00:00|02-08-2022 687 | Ana I. L. Namburete|[INSightR-Net: Interpretable Neural Network for Regression using Similarity-based Comparisons to Prototypical Examples](http://arxiv.org/abs/2208.00457v1)|2022-07-31 15:56:15+00:00|31-07-2022 688 | Dongmei Yu|[Neuro-Symbolic Learning: Principles and Applications in Ophthalmology](http://arxiv.org/abs/2208.00374v1)|2022-07-31 06:48:19+00:00|31-07-2022 689 | Niranjan Balasubramanian|[PASTA: A Dataset for Modeling Participant States in Narratives](http://arxiv.org/abs/2208.00329v1)|2022-07-31 01:21:48+00:00|31-07-2022 690 | 691 | ## 02-08-2022 692 | 693 | main_author|title|update_date|publish_date 694 | ---|---|---|--- 695 | Pietro Lio|[Encoding Concepts in Graph Neural Networks](http://arxiv.org/abs/2207.13586v2)|2022-07-31 20:34:53+00:00|27-07-2022 696 | Nicolas Schönborn|[Explaining Deep Neural Networks for Point Clouds using Gradient-based Visualisations](http://arxiv.org/abs/2207.12984v1)|2022-07-26 15:42:08+00:00|26-07-2022 697 | Stéphanie Maldera|[An Explainable Decision Support System for Predictive Process Analytics](http://arxiv.org/abs/2207.12782v1)|2022-07-26 09:55:49+00:00|26-07-2022 698 | the N3C consortium|[MedML: Fusing Medical Knowledge and Machine Learning Models for Early Pediatric COVID-19 Hospitalization and Severity Prediction](http://arxiv.org/abs/2207.12283v1)|2022-07-25 15:56:14+00:00|25-07-2022 699 | Kejun Wang|[Source Separation of Unknown Numbers of Single-Channel Underwater Acoustic Signals Based on Autoencoders](http://arxiv.org/abs/2207.11749v1)|2022-07-24 14:04:34+00:00|24-07-2022 700 | Min Zhang|[Chunk-aware Alignment and Lexical Constraint for Visual Entailment with Natural Language Explanations](http://arxiv.org/abs/2207.11401v1)|2022-07-23 03:19:50+00:00|23-07-2022 701 | 702 | ## 26-07-2022 703 | 704 | main_author|title|update_date|publish_date 705 | ---|---|---|--- 706 | Yanning Shen|[Explaining Dynamic Graph Neural Networks via Relevance Back-propagation](http://arxiv.org/abs/2207.11175v1)|2022-07-22 16:20:34+00:00|22-07-2022 707 | Deniz Neufeld|[Explainable AI Algorithms for Vibration Data-based Fault Detection: Use Case-adadpted Methods and Critical Evaluation](http://arxiv.org/abs/2207.10732v1)|2022-07-21 19:57:36+00:00|21-07-2022 708 | Jinkyu Kim|[Grounding Visual Representations with Texts for Domain Generalization](http://arxiv.org/abs/2207.10285v1)|2022-07-21 03:43:38+00:00|21-07-2022 709 | Angela Yao|[Discrete-Constrained Regression for Local Counting Models](http://arxiv.org/abs/2207.09865v1)|2022-07-20 12:54:23+00:00|20-07-2022 710 | Navid Asadizanjani|[EVHA: Explainable Vision System for Hardware Testing and Assurance -- An Overview](http://arxiv.org/abs/2207.09627v1)|2022-07-20 02:58:46+00:00|20-07-2022 711 | Alexander Wong|[Towards Trustworthy Healthcare AI: Attention-Based Feature Learning for COVID-19 Screening With Chest Radiography](http://arxiv.org/abs/2207.09312v1)|2022-07-19 14:55:42+00:00|19-07-2022 712 | Nitesh Saxena|[Human Brains Can't Detect Fake News: A Neuro-Cognitive Study of Textual Disinformation Susceptibility](http://arxiv.org/abs/2207.08376v1)|2022-07-18 04:31:07+00:00|18-07-2022 713 | Aparajita Ojha|[Explainable vision transformer enabled convolutional neural network for plant disease identification: PlantXViT](http://arxiv.org/abs/2207.07919v1)|2022-07-16 12:05:06+00:00|16-07-2022 714 | 715 | ## 19-07-2022 716 | 717 | main_author|title|update_date|publish_date 718 | ---|---|---|--- 719 | Hong Liu|[Spatiotemporal Propagation Learning for Network-Wide Flight Delay Prediction](http://arxiv.org/abs/2207.06959v1)|2022-07-14 14:30:59+00:00|14-07-2022 720 | Mennatallah El-Assady|[Beware the Rationalization Trap! When Language Model Explainability Diverges from our Mental Models of Language](http://arxiv.org/abs/2207.06897v1)|2022-07-14 13:26:03+00:00|14-07-2022 721 | Yongdong Zhang|[Explainable Sparse Knowledge Graph Completion via High-order Graph Reasoning Network](http://arxiv.org/abs/2207.07503v1)|2022-07-14 10:16:56+00:00|14-07-2022 722 | Preetum Nakkiran|[Benign, Tempered, or Catastrophic: A Taxonomy of Overfitting](http://arxiv.org/abs/2207.06569v1)|2022-07-14 00:23:01+00:00|14-07-2022 723 | Lianhua Chi|[eX-ViT: A Novel eXplainable Vision Transformer for Weakly Supervised Semantic Segmentation](http://arxiv.org/abs/2207.05358v1)|2022-07-12 07:43:29+00:00|12-07-2022 724 | 725 | ## 12-07-2022 726 | 727 | main_author|title|update_date|publish_date 728 | ---|---|---|--- 729 | Thomas Wolf|[Training Transformers Together](http://arxiv.org/abs/2207.03481v1)|2022-07-07 17:59:16+00:00|07-07-2022 730 | Dinh Phung|[An Additive Instance-Wise Approach to Multi-class Model Interpretation](http://arxiv.org/abs/2207.03113v1)|2022-07-07 06:50:27+00:00|07-07-2022 731 | Ge Zhang|[Correlation between entropy and generalizability in a neural network](http://arxiv.org/abs/2207.01996v1)|2022-07-05 12:28:13+00:00|05-07-2022 732 | Ben Glocker|[Hierarchical Symbolic Reasoning in Hyperbolic Space for Deep Discriminative Models](http://arxiv.org/abs/2207.01916v1)|2022-07-05 09:51:39+00:00|05-07-2022 733 | Phillippa Spencer|[Explainability in Deep Reinforcement Learning, a Review into Current Methods and Applications](http://arxiv.org/abs/2207.01911v1)|2022-07-05 09:43:17+00:00|05-07-2022 734 | Zhen Li|[Toward Explainable and Fine-Grained 3D Grounding through Referring Textual Phrases](http://arxiv.org/abs/2207.01821v1)|2022-07-05 05:50:12+00:00|05-07-2022 735 | Christian Nolde|[Fidelity of Ensemble Aggregation for Saliency Map Explanations using Bayesian Optimization Techniques](http://arxiv.org/abs/2207.01565v2)|2022-07-05 06:42:09+00:00|04-07-2022 736 | 737 | ## 05-07-2022 738 | 739 | main_author|title|update_date|publish_date 740 | ---|---|---|--- 741 | Farzad Khalvati|[Improving Disease Classification Performance and Explainability of Deep Learning Models in Radiology with Heatmap Generators](http://arxiv.org/abs/2207.00157v1)|2022-06-28 13:03:50+00:00|28-06-2022 742 | Reinhard Heil|[Explaining Any ML Model? -- On Goals and Capabilities of XAI](http://arxiv.org/abs/2206.13888v1)|2022-06-28 11:09:33+00:00|28-06-2022 743 | Pratyush Tiwary|[Thermodynamics of Interpretation](http://arxiv.org/abs/2206.13475v1)|2022-06-27 17:36:50+00:00|27-06-2022 744 | Dominik Janzing|[Explaining the root causes of unit-level changes](http://arxiv.org/abs/2206.12986v1)|2022-06-26 22:32:11+00:00|26-06-2022 745 | Navin Kumar|[Explainable and High-Performance Hate and Offensive Speech Detection](http://arxiv.org/abs/2206.12983v1)|2022-06-26 22:02:53+00:00|26-06-2022 746 | Zheng Zhang|[Self-Healing Robust Neural Networks via Closed-Loop Control](http://arxiv.org/abs/2206.12963v1)|2022-06-26 20:25:35+00:00|26-06-2022 747 | Zihao Zhu|[From Shallow to Deep: Compositional Reasoning over Graphs for Visual Question Answering](http://arxiv.org/abs/2206.12533v1)|2022-06-25 02:20:02+00:00|25-06-2022 748 | 749 | ## 28-06-2022 750 | 751 | main_author|title|update_date|publish_date 752 | ---|---|---|--- 753 | Jin Song Dong|[Adversarial Robustness of Deep Neural Networks: A Survey from a Formal Verification Perspective](http://arxiv.org/abs/2206.12227v1)|2022-06-24 11:53:12+00:00|24-06-2022 754 | Ioannis Mitliagkas|[Optimal transport meets noisy label robust loss and MixUp regularization for domain adaptation](http://arxiv.org/abs/2206.11180v1)|2022-06-22 15:40:52+00:00|22-06-2022 755 | Heng Tao Shen|[KE-RCNN: Unifying Knowledge based Reasoning into Part-level Attribute Parsing](http://arxiv.org/abs/2206.10146v1)|2022-06-21 07:05:14+00:00|21-06-2022 756 | Joao Marques-Silva|[Eliminating The Impossible, Whatever Remains Must Be True](http://arxiv.org/abs/2206.09551v1)|2022-06-20 03:18:14+00:00|20-06-2022 757 | Shixia Liu|[A Unified Understanding of Deep NLP Models for Text Classification](http://arxiv.org/abs/2206.09355v1)|2022-06-19 08:55:07+00:00|19-06-2022 758 | Ajitesh Srivastava|[Random Forest of Epidemiological Models for Influenza Forecasting](http://arxiv.org/abs/2206.08967v1)|2022-06-17 18:47:40+00:00|17-06-2022 759 | 760 | ## 21-06-2022 761 | 762 | main_author|title|update_date|publish_date 763 | ---|---|---|--- 764 | Allan Tucker|[Leveraging Uncertainty in Deep Learning for Pancreatic Adenocarcinoma Grading](http://arxiv.org/abs/2206.08787v1)|2022-06-15 19:53:06+00:00|15-06-2022 765 | Przemysław Biecek|[Explainable expected goal models for performance analysis in football analytics](http://arxiv.org/abs/2206.07212v1)|2022-06-14 23:56:03+00:00|14-06-2022 766 | Kristian Kersting|[Machines Explaining Linear Programs](http://arxiv.org/abs/2206.07194v1)|2022-06-14 22:52:25+00:00|14-06-2022 767 | 768 | ## 15-06-2022 769 | 770 | main_author|title|update_date|publish_date 771 | ---|---|---|--- 772 | Bernd Bischl|[Enhancing Explainability of Hyperparameter Optimization via Bayesian Algorithm Execution](http://arxiv.org/abs/2206.05447v1)|2022-06-11 07:12:04+00:00|11-06-2022 773 | 774 | ## 14-06-2022 775 | 776 | main_author|title|update_date|publish_date 777 | ---|---|---|--- 778 | Michael Pazzani|[Explaining Image Classifiers Using Contrastive Counterfactuals in Generative Latent Spaces](http://arxiv.org/abs/2206.05257v1)|2022-06-10 17:54:46+00:00|10-06-2022 779 | Oliver Speck|[Weakly-supervised segmentation using inherently-explainable classification models and their application to brain tumour classification](http://arxiv.org/abs/2206.05148v1)|2022-06-10 14:44:05+00:00|10-06-2022 780 | Shixia Liu|[Diagnosing Ensemble Few-Shot Classifiers](http://arxiv.org/abs/2206.04372v1)|2022-06-09 09:29:18+00:00|09-06-2022 781 | Md Esharuzzaman Emu|[Predictions of Electromotive Force of Magnetic Shape Memory Alloy (MSMA) Using Constitutive Model and Generalized Regression Neural Network](http://arxiv.org/abs/2206.03701v1)|2022-06-08 06:38:33+00:00|08-06-2022 782 | Sebastian Lapuschkin|"[From ""Where"" to ""What"": Towards Human-Understandable Explanations through Concept Relevance Propagation](http://arxiv.org/abs/2206.03208v1)"|2022-06-07 12:05:58+00:00|07-06-2022 783 | Suat Ozdemir|[Explainable Artificial Intelligence (XAI) for Internet of Things: A Survey](http://arxiv.org/abs/2206.04800v1)|2022-06-07 08:22:30+00:00|07-06-2022 784 | Tamir Hazan|[Dual Decomposition of Convex Optimization Layers for Consistent Attention in Medical Images](http://arxiv.org/abs/2206.02761v2)|2022-06-07 14:07:51+00:00|06-06-2022 785 | Phillippa Spencer|[Robust Adversarial Attacks Detection based on Explainable Deep Reinforcement Learning For UAV Guidance and Planning](http://arxiv.org/abs/2206.02670v2)|2022-06-07 10:18:03+00:00|06-06-2022 786 | Christian W. Omlin|[Towards Responsible AI for Financial Transactions](http://arxiv.org/abs/2206.02419v1)|2022-06-06 08:29:47+00:00|06-06-2022 787 | Tat-Seng Chua|[Invariant Grounding for Video Question Answering](http://arxiv.org/abs/2206.02349v1)|2022-06-06 04:37:52+00:00|06-06-2022 788 | Liz Sonenberg|[Improving Model Understanding and Trust with Counterfactual Explanations of Model Confidence](http://arxiv.org/abs/2206.02790v1)|2022-06-06 04:04:28+00:00|06-06-2022 789 | Shahana Akter Luna|[Image Data collection and implementation of deep learning-based model in detecting Monkeypox disease using modified VGG16](http://arxiv.org/abs/2206.01862v1)|2022-06-04 00:34:15+00:00|04-06-2022 790 | 791 | ## 07-06-2022 792 | 793 | main_author|title|update_date|publish_date 794 | ---|---|---|--- 795 | Stefan Wagner|[Can Requirements Engineering Support Explainable Artificial Intelligence? Towards a User-Centric Approach for Explainability Requirements](http://arxiv.org/abs/2206.01507v1)|2022-06-03 11:17:41+00:00|03-06-2022 796 | Reinhard Heckel|[Regularization-wise double descent: Why it occurs and how to eliminate it](http://arxiv.org/abs/2206.01378v1)|2022-06-03 03:23:58+00:00|03-06-2022 797 | Michael T. Lash|[HEX: Human-in-the-loop Explainability via Deep Reinforcement Learning](http://arxiv.org/abs/2206.01343v1)|2022-06-02 23:53:40+00:00|02-06-2022 798 | Guillaume Lajoie|[Beyond accuracy: generalization properties of bio-plausible temporal credit assignment rules](http://arxiv.org/abs/2206.00823v1)|2022-06-02 01:39:08+00:00|02-06-2022 799 | Amulya Yadav|[RoCourseNet: Distributionally Robust Training of a Prediction Aware Recourse Model](http://arxiv.org/abs/2206.00700v1)|2022-06-01 18:18:18+00:00|01-06-2022 800 | Christian Daul|[Interpretable Deep Learning Classifier by Detection of Prototypical Parts on Kidney Stones Images](http://arxiv.org/abs/2206.00252v2)|2022-06-02 03:06:35+00:00|01-06-2022 801 | Tim van Erven|[Attribution-based Explanations that Provide Recourse Cannot be Robust](http://arxiv.org/abs/2205.15834v1)|2022-05-31 14:37:39+00:00|31-05-2022 802 | Vladimir Cherkassky|[VC Theoretical Explanation of Double Descent](http://arxiv.org/abs/2205.15549v1)|2022-05-31 05:50:02+00:00|31-05-2022 803 | Hung-yi Lee|[Searching for the Essence of Adversarial Perturbations](http://arxiv.org/abs/2205.15357v1)|2022-05-30 18:04:57+00:00|30-05-2022 804 | Taiji Suzuki|[Excess Risk of Two-Layer ReLU Neural Networks in Teacher-Student Settings and its Superiority to Kernel Methods](http://arxiv.org/abs/2205.14818v2)|2022-06-06 14:29:46+00:00|30-05-2022 805 | 806 | ## 31-05-2022 807 | 808 | main_author|title|update_date|publish_date 809 | ---|---|---|--- 810 | Suhang Wang|[On Consistency in Graph Neural Network Interpretation](http://arxiv.org/abs/2205.13733v1)|2022-05-27 02:58:07+00:00|27-05-2022 811 | Gugan Thoppe|[Approximate Q-learning and SARSA(0) under the $ε$-greedy Policy: a Differential Inclusion Analysis](http://arxiv.org/abs/2205.13617v1)|2022-05-26 20:46:01+00:00|26-05-2022 812 | Xiaoying Tang|[FedAug: Reducing the Local Learning Bias Improves Federated Learning on Heterogeneous Data](http://arxiv.org/abs/2205.13462v2)|2022-05-27 09:57:25+00:00|26-05-2022 813 | Jing Xiao|[Leveraging Causal Inference for Explainable Automatic Program Repair](http://arxiv.org/abs/2205.13342v1)|2022-05-26 13:25:33+00:00|26-05-2022 814 | Roger Wattenhofer|[DT+GNN: A Fully Explainable Graph Neural Network using Decision Trees](http://arxiv.org/abs/2205.13234v1)|2022-05-26 09:01:50+00:00|26-05-2022 815 | Sarem Seitz|[Gradient-based explanations for Gaussian Process regression and classification models](http://arxiv.org/abs/2205.12797v1)|2022-05-25 14:11:00+00:00|25-05-2022 816 | Xiang Ren|[ER-TEST: Evaluating Explanation Regularization Methods for NLP Models](http://arxiv.org/abs/2205.12542v1)|2022-05-25 07:31:43+00:00|25-05-2022 817 | Lifu Huang|[End-to-End Multimodal Fact-Checking and Explanation Generation: A Challenging Dataset and Models](http://arxiv.org/abs/2205.12487v1)|2022-05-25 04:36:46+00:00|25-05-2022 818 | Art B. Owen|[Deletion and Insertion Tests in Regression Models](http://arxiv.org/abs/2205.12423v1)|2022-05-25 00:55:47+00:00|25-05-2022 819 | Marzieh Saeidi|[Policy Compliance Detection via Expression Tree Inference](http://arxiv.org/abs/2205.12259v1)|2022-05-24 17:59:31+00:00|24-05-2022 820 | Pablo Lemos|[Split personalities in Bayesian Neural Networks: the case for full marginalisation](http://arxiv.org/abs/2205.11151v1)|2022-05-23 09:24:37+00:00|23-05-2022 821 | Walid Saad|[Neuro-Symbolic Artificial Intelligence (AI) for Intent based Semantic Communication](http://arxiv.org/abs/2205.10768v1)|2022-05-22 07:11:57+00:00|22-05-2022 822 | 823 | ## 24-05-2022 824 | 825 | main_author|title|update_date|publish_date 826 | ---|---|---|--- 827 | Marcus Kalander|[RiskLoc: Localization of Multi-dimensional Root Causes by Weighted Risk](http://arxiv.org/abs/2205.10004v1)|2022-05-20 07:43:18+00:00|20-05-2022 828 | Narayanan C Krishnan|[Explainable Supervised Domain Adaptation](http://arxiv.org/abs/2205.09943v1)|2022-05-20 03:33:04+00:00|20-05-2022 829 | Dan Roth|[Entailment Tree Explanations via Iterative Retrieval-Generation Reasoner](http://arxiv.org/abs/2205.09224v1)|2022-05-18 21:52:11+00:00|18-05-2022 830 | Fariza Sabrina|[Explainable and Optimally Configured Artificial Neural Networks for Attack Detection in Smart Homes](http://arxiv.org/abs/2205.08043v1)|2022-05-17 01:25:32+00:00|17-05-2022 831 | Yingjun Deng|[Exploring the Learning Difficulty of Data Theory and Measure](http://arxiv.org/abs/2205.07427v1)|2022-05-16 02:28:12+00:00|16-05-2022 832 | 833 | ## 17-05-2022 834 | 835 | main_author|title|update_date|publish_date 836 | ---|---|---|--- 837 | Christoph M. Friedrich|[Machine Learning Workflow to Explain Black-box Models for Early Alzheimer's Disease Classification Evaluated for Multiple Datasets](http://arxiv.org/abs/2205.05907v1)|2022-05-12 06:58:11+00:00|12-05-2022 838 | Bing Qin|[e-CARE: a New Dataset for Exploring Explainable Causal Reasoning](http://arxiv.org/abs/2205.05849v1)|2022-05-12 02:41:48+00:00|12-05-2022 839 | Jingge Zhu|[On Causality in Domain Adaptation and Semi-Supervised Learning: an Information-Theoretic Analysis](http://arxiv.org/abs/2205.04641v1)|2022-05-10 03:18:48+00:00|10-05-2022 840 | Marzyeh Ghassemi|[The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations](http://arxiv.org/abs/2205.03295v1)|2022-05-06 15:23:32+00:00|06-05-2022 841 | Changshui Zhang|[METGEN: A Module-Based Entailment Tree Generation Framework for Answer Explanation](http://arxiv.org/abs/2205.02593v1)|2022-05-05 12:06:02+00:00|05-05-2022 842 | Yongxin Guo|[InvNorm: Domain Generalization for Object Detection in Gastrointestinal Endoscopy](http://arxiv.org/abs/2205.02842v1)|2022-05-05 03:47:23+00:00|05-05-2022 843 | Ji-Rong Wen|[Great Truths are Always Simple: A Rather Simple Knowledge Encoder for Enhancing the Commonsense Reasoning Capacity of Pre-Trained Models](http://arxiv.org/abs/2205.01841v1)|2022-05-04 01:27:36+00:00|04-05-2022 844 | André Freitas|[Scientific Explanation and Natural Language: A Unified Epistemological-Linguistic Perspective for Explainable AI](http://arxiv.org/abs/2205.01809v2)|2022-05-05 05:37:58+00:00|03-05-2022 845 | Laurent Charlin|[Foundational Models for Continual Learning: An Empirical Study of Latent Replay](http://arxiv.org/abs/2205.00329v1)|2022-04-30 19:11:37+00:00|30-04-2022 846 | Nasir Ahmad|[An Explainable Regression Framework for Predicting Remaining Useful Life of Machines](http://arxiv.org/abs/2204.13574v2)|2022-04-30 08:58:04+00:00|28-04-2022 847 | Angela Yao|[A Closer Look at Branch Classifiers of Multi-exit Architectures](http://arxiv.org/abs/2204.13347v1)|2022-04-28 08:37:25+00:00|28-04-2022 848 | Tim Landgraf|[Do Users Benefit From Interpretable Vision? A User Study, Baseline, And Dataset](http://arxiv.org/abs/2204.11642v1)|2022-04-25 13:20:06+00:00|25-04-2022 849 | Aparna Bhonde|[Farmer's Assistant: A Machine Learning Based Application for Agricultural Solutions](http://arxiv.org/abs/2204.11340v1)|2022-04-24 19:31:10+00:00|24-04-2022 850 | Lexing Ying|[The Multiscale Structure of Neural Network Loss Functions: The Effect on Optimization and Origin](http://arxiv.org/abs/2204.11326v2)|2022-05-11 03:53:29+00:00|24-04-2022 851 | Alexander Wong|[COVID-Net Biochem: An Explainability-driven Framework to Building Machine Learning Models for Predicting Survival and Kidney Injury of COVID-19 Patients from Clinical and Biochemistry Data](http://arxiv.org/abs/2204.11210v1)|2022-04-24 07:38:37+00:00|24-04-2022 852 | Risto Miikkulainen|[Evolution of Transparent Explainable Rule-sets](http://arxiv.org/abs/2204.10438v1)|2022-04-21 23:59:17+00:00|21-04-2022 853 | Giacomo Boracchi|[Perception Visualization: Seeing Through the Eyes of a DNN](http://arxiv.org/abs/2204.09920v1)|2022-04-21 07:18:55+00:00|21-04-2022 854 | Suhang Wang|[A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability](http://arxiv.org/abs/2204.08570v1)|2022-04-18 21:41:07+00:00|18-04-2022 855 | Mark Riedl|[Calibrating Trust of Multi-Hop Question Answering Systems with Decompositional Probes](http://arxiv.org/abs/2204.07693v1)|2022-04-16 01:03:36+00:00|16-04-2022 856 | Helge Gillmeister|[EEG-ITNet: An Explainable Inception Temporal Convolutional Network for Motor Imagery Classification](http://arxiv.org/abs/2204.06947v1)|2022-04-14 13:18:43+00:00|14-04-2022 857 | André Freitas|[Assessing the communication gap between AI models and healthcare professionals: explainability, utility and trust in AI-driven clinical decision-making](http://arxiv.org/abs/2204.05030v2)|2022-04-13 19:49:46+00:00|11-04-2022 858 | Manoj Himmatrao Devare|[Optimization of IoT-Enabled Physical Location Monitoring Using DT and VAR](http://arxiv.org/abs/2204.04664v1)|2022-04-10 11:39:46+00:00|10-04-2022 859 | Stefan Wermter|[Explain yourself! Effects of Explanations in Human-Robot Interaction](http://arxiv.org/abs/2204.04501v1)|2022-04-09 15:54:27+00:00|09-04-2022 860 | Reza Safabakhsh|[Using Decision Tree as Local Interpretable Model in Autoencoder-based LIME](http://arxiv.org/abs/2204.03321v1)|2022-04-07 09:39:02+00:00|07-04-2022 861 | Diyi Yang|[The Moral Integrity Corpus: A Benchmark for Ethical Dialogue Systems](http://arxiv.org/abs/2204.03021v1)|2022-04-06 18:10:53+00:00|06-04-2022 862 | Ute Schmid|[CAIPI in Practice: Towards Explainable Interactive Medical Image Classification](http://arxiv.org/abs/2204.02661v1)|2022-04-06 08:21:34+00:00|06-04-2022 863 | David Lo|[An Exploratory Study on Code Attention in BERT](http://arxiv.org/abs/2204.10200v1)|2022-04-05 21:23:10+00:00|05-04-2022 864 | Lucy Youngmin Eun|[Explainable Deep Learning Algorithm for Distinguishing Incomplete Kawasaki Disease by Coronary Artery Lesions on Echocardiographic Imaging](http://arxiv.org/abs/2204.02403v1)|2022-04-05 11:39:02+00:00|05-04-2022 865 | Claudio Angione|[A pipeline and comparative study of 12 machine learning models for text classification](http://arxiv.org/abs/2204.06518v1)|2022-04-04 23:51:22+00:00|04-04-2022 866 | Tao Mei|[A-ACT: Action Anticipation through Cycle Transformations](http://arxiv.org/abs/2204.00942v1)|2022-04-02 21:50:45+00:00|02-04-2022 867 | Subir Kumar Saha|[Interpretation of Black Box NLP Models: A Survey](http://arxiv.org/abs/2203.17081v1)|2022-03-31 14:54:35+00:00|31-03-2022 868 | Nassir Navab|[Interpretable Vertebral Fracture Diagnosis](http://arxiv.org/abs/2203.16273v1)|2022-03-30 13:07:41+00:00|30-03-2022 869 | Shih-Fu Chang|[Fine-Grained Visual Entailment](http://arxiv.org/abs/2203.15704v1)|2022-03-29 16:09:38+00:00|29-03-2022 870 | Baochun Li|[OrphicX: A Causality-Inspired Latent Variable Model for Interpreting Graph Neural Networks](http://arxiv.org/abs/2203.15209v1)|2022-03-29 03:08:33+00:00|29-03-2022 871 | Yi Yang|[Visual Abductive Reasoning](http://arxiv.org/abs/2203.14040v1)|2022-03-26 10:17:03+00:00|26-03-2022 872 | Gesina Schwalbe|[Concept Embedding Analysis: A Review](http://arxiv.org/abs/2203.13909v1)|2022-03-25 20:57:16+00:00|25-03-2022 873 | Dawn Sepehr|[Gender and Racial Stereotype Detection in Legal Opinion Word Embeddings](http://arxiv.org/abs/2203.13369v2)|2022-04-12 00:58:47+00:00|24-03-2022 874 | P. A. N. Bosman|[Multi-modal multi-objective model-based genetic programming to find multiple diverse high-quality models](http://arxiv.org/abs/2203.13347v1)|2022-03-24 21:35:07+00:00|24-03-2022 875 | David Blei|[Estimating Social Influence from Observational Data](http://arxiv.org/abs/2204.01633v1)|2022-03-24 20:21:24+00:00|24-03-2022 876 | Kerstin Ritter|[Feature visualization for convolutional neural network models trained on neuroimaging data](http://arxiv.org/abs/2203.13120v1)|2022-03-24 15:24:38+00:00|24-03-2022 877 | Alberto Del Bimbo|[SMEMO: Social Memory for Trajectory Forecasting](http://arxiv.org/abs/2203.12446v1)|2022-03-23 14:40:20+00:00|23-03-2022 878 | Michael Witbrock|[AbductionRules: Training Transformers to Explain Unexpected Inputs](http://arxiv.org/abs/2203.12186v1)|2022-03-23 04:18:30+00:00|23-03-2022 879 | Steffen Eger|[Towards Explainable Evaluation Metrics for Natural Language Generation](http://arxiv.org/abs/2203.11131v1)|2022-03-21 17:05:54+00:00|21-03-2022 880 | Honghan Wu|[Automated Clinical Coding: What, Why, and Where We Are?](http://arxiv.org/abs/2203.11092v1)|2022-03-21 16:17:38+00:00|21-03-2022 881 | Ivana Dusparic|[ReCCoVER: Detecting Causal Confusion for Explainable Reinforcement Learning](http://arxiv.org/abs/2203.11211v1)|2022-03-21 13:17:30+00:00|21-03-2022 882 | Johan W. Verjans|[CNN Attention Guidance for Improved Orthopedics Radiographic Fracture Classification](http://arxiv.org/abs/2203.10690v1)|2022-03-21 01:07:42+00:00|21-03-2022 883 | Miguel Angel Gonzalez Ballester|[Attri-VAE: attribute-based, disentangled and interpretable representations of medical images with variational autoencoders](http://arxiv.org/abs/2203.10417v2)|2022-03-27 06:16:56+00:00|20-03-2022 884 | Wei Lu|[Learning to Reason Deductively: Math Word Problem Solving as Complex Relation Extraction](http://arxiv.org/abs/2203.10316v3)|2022-04-25 06:54:02+00:00|19-03-2022 885 | Hao Zhou|[E-KAR: A Benchmark for Rationalizing Natural Language Analogical Reasoning](http://arxiv.org/abs/2203.08480v1)|2022-03-16 09:16:38+00:00|16-03-2022 886 | Oladimeji Farri|[Differentiable Multi-Agent Actor-Critic for Multi-Step Radiology Report Summarization](http://arxiv.org/abs/2203.08257v2)|2022-04-29 21:08:05+00:00|15-03-2022 887 | Wojciech Samek|[Beyond Explaining: Opportunities and Challenges of XAI-Based Model Improvement](http://arxiv.org/abs/2203.08008v1)|2022-03-15 15:44:28+00:00|15-03-2022 888 | Prithviraj Ammanabrolu|[ScienceWorld: Is your Agent Smarter than a 5th Grader?](http://arxiv.org/abs/2203.07540v1)|2022-03-14 22:52:34+00:00|14-03-2022 889 | Christopher Mutschler|[Don't Get Me Wrong: How to apply Deep Visual Interpretations to Time Series](http://arxiv.org/abs/2203.07861v1)|2022-03-14 15:22:20+00:00|14-03-2022 890 | Shafiq Joty|[Chart-to-Text: A Large-Scale Benchmark for Chart Summarization](http://arxiv.org/abs/2203.06486v3)|2022-04-14 15:41:15+00:00|12-03-2022 891 | Qi Zhao|[REX: Reasoning-aware and Grounded Explanation](http://arxiv.org/abs/2203.06107v1)|2022-03-11 17:28:42+00:00|11-03-2022 892 | Pok Wah Chan|[DeepTrust: A Reliable Financial Knowledge Retrieval Framework For Explaining Extreme Pricing Anomalies](http://arxiv.org/abs/2203.08144v1)|2022-03-11 06:29:22+00:00|11-03-2022 893 | Nikos Deligiannis|[NLX-GPT: A Model for Natural Language Explanations in Vision and Vision-Language Tasks](http://arxiv.org/abs/2203.05081v1)|2022-03-09 22:57:15+00:00|09-03-2022 894 | Nassir Navab|[Do Explanations Explain? Model Knows Best](http://arxiv.org/abs/2203.02269v1)|2022-03-04 12:39:29+00:00|04-03-2022 895 | Tomas Pfister|[Data-Efficient and Interpretable Tabular Anomaly Detection](http://arxiv.org/abs/2203.02034v1)|2022-03-03 22:02:56+00:00|03-03-2022 896 | Louis-Philippe Morency|[DIME: Fine-grained Interpretations of Multimodal Models via Disentangled Local Explanations](http://arxiv.org/abs/2203.02013v1)|2022-03-03 20:52:47+00:00|03-03-2022 897 | Yukie Nagai|[The world seems different in a social context: a neural network analysis of human experimental data](http://arxiv.org/abs/2203.01862v1)|2022-03-03 17:19:12+00:00|03-03-2022 898 | Ali Sunyaev|[Why Do Machine Learning Practitioners Still Use Manual Tuning? A Qualitative Study](http://arxiv.org/abs/2203.01717v1)|2022-03-03 13:55:38+00:00|03-03-2022 899 | David Masip|[ADVISE: ADaptive Feature Relevance and VISual Explanations for Convolutional Neural Networks](http://arxiv.org/abs/2203.01289v1)|2022-03-02 18:16:57+00:00|02-03-2022 900 | Timothée Lesort|[Continual Feature Selection: Spurious Features in Continual Learning](http://arxiv.org/abs/2203.01012v1)|2022-03-02 10:43:54+00:00|02-03-2022 901 | Marc G. Bellemare|[On the Generalization of Representations in Reinforcement Learning](http://arxiv.org/abs/2203.00543v1)|2022-03-01 15:22:09+00:00|01-03-2022 902 | Anastasios M. Lekkas|[Approximating a deep reinforcement learning docking agent using linear model trees](http://arxiv.org/abs/2203.00369v1)|2022-03-01 11:32:07+00:00|01-03-2022 903 | Bryan Kian Hsiang Low|[Markov Chain Monte Carlo-Based Machine Unlearning: Unlearning What Needs to be Forgotten](http://arxiv.org/abs/2202.13585v1)|2022-02-28 07:14:34+00:00|28-02-2022 904 | Dongsoo Har|[Sensing accident-prone features in urban scenes for proactive driving and accident prevention](http://arxiv.org/abs/2202.12788v1)|2022-02-25 16:05:53+00:00|25-02-2022 905 | Zhe Hou|[MUC-driven Feature Importance Measurement and Adversarial Analysis for Random Forest](http://arxiv.org/abs/2202.12512v1)|2022-02-25 06:15:47+00:00|25-02-2022 906 | Tianbao Yang|[Provable Stochastic Optimization for Global Contrastive Learning: Small Batch Does Not Harm Performance](http://arxiv.org/abs/2202.12387v1)|2022-02-24 22:16:53+00:00|24-02-2022 907 | Marco F. Huber|[XAutoML: A Visual Analytics Tool for Establishing Trust in Automated Machine Learning](http://arxiv.org/abs/2202.11954v1)|2022-02-24 08:18:25+00:00|24-02-2022 908 | Mohit Prabhushankar|[Explanatory Paradigms in Neural Networks](http://arxiv.org/abs/2202.11838v1)|2022-02-24 00:22:11+00:00|24-02-2022 909 | T. Östreich|[Deep Learning Reproducibility and Explainable AI (XAI)](http://arxiv.org/abs/2202.11452v3)|2022-03-02 09:52:11+00:00|23-02-2022 910 | Shiliang Pu|[Learning Multiple Explainable and Generalizable Cues for Face Anti-spoofing](http://arxiv.org/abs/2202.10187v1)|2022-02-21 12:55:59+00:00|21-02-2022 911 | N. Asokan|[Do Transformers use variable binding?](http://arxiv.org/abs/2203.00162v2)|2022-03-15 15:54:04+00:00|19-02-2022 912 | Yongfeng Zhang|[Learning and Evaluating Graph Neural Network Explanations based on Counterfactual and Factual Reasoning](http://arxiv.org/abs/2202.08816v3)|2022-05-10 21:26:14+00:00|17-02-2022 913 | A. Aldo Faisal|[The Response Shift Paradigm to Quantify Human Trust in AI Recommendations](http://arxiv.org/abs/2202.08979v1)|2022-02-16 22:02:09+00:00|16-02-2022 914 | Manfred Reichert|[XAI in the context of Predictive Process Monitoring: Too much to Reveal](http://arxiv.org/abs/2202.08265v1)|2022-02-16 15:31:59+00:00|16-02-2022 915 | Manfred Reichert|[Explainability of Predictive Process Monitoring Results: Can You See My Data Issues?](http://arxiv.org/abs/2202.08041v1)|2022-02-16 13:14:02+00:00|16-02-2022 916 | Shangsong Liang|[Revisiting Parameter-Efficient Tuning: Are We Really There Yet?](http://arxiv.org/abs/2202.07962v1)|2022-02-16 10:11:19+00:00|16-02-2022 917 | Li Chen|[Personalized Prompt Learning for Explainable Recommendation](http://arxiv.org/abs/2202.07371v1)|2022-02-15 12:53:52+00:00|15-02-2022 918 | Marina M. -C. Höhne|[Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations](http://arxiv.org/abs/2202.06861v1)|2022-02-14 16:45:36+00:00|14-02-2022 919 | Md Rafiqul Islam Rabin|[Extracting Label-specific Key Input Features for Neural Code Intelligence Models](http://arxiv.org/abs/2202.06474v1)|2022-02-14 03:36:35+00:00|14-02-2022 920 | Marcus Liwicki|[HaT5: Hate Language Identification using Text-to-Text Transfer Transformer](http://arxiv.org/abs/2202.05690v1)|2022-02-11 15:21:27+00:00|11-02-2022 921 | Bo Xu|[Motif-topology and Reward-learning improved Spiking Neural Network for Efficient Multi-sensory Integration](http://arxiv.org/abs/2202.06821v1)|2022-02-11 02:07:44+00:00|11-02-2022 922 | Giovanni Iacca|[Interpretable pipelines with evolutionarily optimized modules for RL tasks with visual inputs](http://arxiv.org/abs/2202.04943v1)|2022-02-10 10:33:44+00:00|10-02-2022 923 | Graeme Burt|[Explainable Machine Learning for Breakdown Prediction in High Gradient RF Cavities](http://arxiv.org/abs/2202.05610v1)|2022-02-10 07:32:18+00:00|10-02-2022 924 | David A. Clifton|[How to Understand Masked Autoencoders](http://arxiv.org/abs/2202.03670v2)|2022-02-09 18:33:57+00:00|08-02-2022 925 | Sanjay Shakkottai|[MAML and ANIL Provably Learn Representations](http://arxiv.org/abs/2202.03483v1)|2022-02-07 19:43:02+00:00|07-02-2022 926 | Stan Z. Li|[SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation](http://arxiv.org/abs/2202.03104v2)|2022-02-11 15:26:05+00:00|07-02-2022 927 | Yang Liu|[Identifiability of Label Noise Transition Matrix](http://arxiv.org/abs/2202.02016v2)|2022-04-08 08:03:05+00:00|04-02-2022 928 | Jörg Hähner|[Separating Rule Discovery and Global Solution Composition in a Learning Classifier System](http://arxiv.org/abs/2202.01677v2)|2022-04-18 20:07:32+00:00|03-02-2022 929 | Samuel Yen-Chi Chen|[Financial Vision Based Reinforcement Learning Trading Strategy](http://arxiv.org/abs/2202.04115v1)|2022-02-03 02:14:38+00:00|03-02-2022 930 | Amal Zouaq|[Toward a traceable, explainable, and fairJD/Resume recommendation system](http://arxiv.org/abs/2202.08960v1)|2022-02-02 18:17:05+00:00|02-02-2022 931 | Marco Huber|[Feature Visualization within an Automated Design Assessment leveraging Explainable Artificial Intelligence Methods](http://arxiv.org/abs/2201.12107v1)|2022-01-28 13:31:42+00:00|28-01-2022 932 | Xiaoyong Wei|[Indicative Image Retrieval: Turning Blackbox Learning into Grey](http://arxiv.org/abs/2201.11898v2)|2022-03-16 09:29:23+00:00|28-01-2022 933 | Hamid R. Rabiee|[LAP: An Attention-Based Module for Faithful Interpretation and Knowledge Injection in Convolutional Neural Networks](http://arxiv.org/abs/2201.11808v2)|2022-03-14 10:30:27+00:00|27-01-2022 934 | Ivan Vulić|[IGLUE: A Benchmark for Transfer Learning across Modalities, Tasks, and Languages](http://arxiv.org/abs/2201.11732v1)|2022-01-27 18:53:22+00:00|27-01-2022 935 | Friedrich T. Sommer|[A probabilistic latent variable model for detecting structure in binary data](http://arxiv.org/abs/2201.11108v1)|2022-01-26 18:37:35+00:00|26-01-2022 936 | Manuel Moussallam|[Explainability in Music Recommender Systems](http://arxiv.org/abs/2201.10528v1)|2022-01-25 18:32:11+00:00|25-01-2022 937 | Ali Emami|[An Application of Pseudo-Log-Likelihoods to Natural Language Scoring](http://arxiv.org/abs/2201.09377v1)|2022-01-23 22:00:54+00:00|23-01-2022 938 | Praveen Ranjan Srivastava|[Causal effect of racial bias in data and machine learning algorithms on user persuasiveness & discriminatory decision making: An Empirical Study](http://arxiv.org/abs/2202.00471v2)|2022-02-02 03:20:41+00:00|22-01-2022 939 | Tat-Seng Chua|[Deconfounding to Explanation Evaluation in Graph Neural Networks](http://arxiv.org/abs/2201.08802v3)|2022-02-01 05:41:39+00:00|21-01-2022 940 | Enrico Bertini|[Visual Exploration of Machine Learning Model Behavior with Hierarchical Surrogate Rule Sets](http://arxiv.org/abs/2201.07724v1)|2022-01-19 17:03:35+00:00|19-01-2022 941 | Sergey Ivanov|[Reinforcement Learning Textbook](http://arxiv.org/abs/2201.09746v1)|2022-01-19 15:54:39+00:00|19-01-2022 942 | Jianmin Wang|[Inferring Commonsense Explanations as Prompts for Future Event Generation](http://arxiv.org/abs/2201.07099v1)|2022-01-18 16:21:23+00:00|18-01-2022 943 | Johannes Schmidt-Hieber|[On generalization bounds for deep networks based on loss surface implicit regularization](http://arxiv.org/abs/2201.04545v1)|2022-01-12 16:41:34+00:00|12-01-2022 944 | Yangfeng Ji|[Explaining Prediction Uncertainty of Pre-trained Language Models by Detecting Uncertain Words in Inputs](http://arxiv.org/abs/2201.03742v1)|2022-01-11 02:04:50+00:00|11-01-2022 945 | Lester Beltran|[A Planck Radiation and Quantization Scheme for Human Cognition and Language](http://arxiv.org/abs/2201.03306v2)|2022-03-04 10:31:22+00:00|10-01-2022 946 | 947 | ## 10-05-2022 948 | 949 | main_author|title|update_date|publish_date 950 | ---|---|---|--- 951 | Sheraz Ahmed|[ExAID: A Multimodal Explanation Framework for Computer-Aided Diagnosis of Skin Lesions](http://arxiv.org/abs/2201.01249v1)|2022-01-04 17:11:28+00:00|04-01-2022 952 | 953 | ## 04-05-2022 954 | 955 | main_author|title|update_date|publish_date 956 | ---|---|---|--- 957 | Sheraz Ahmed|[ExAID: A Multimodal Explanation Framework for Computer-Aided Diagnosis of Skin Lesions](http://arxiv.org/abs/2201.01249v1)|2022-01-04 17:11:28+00:00|04-01-2022 958 | 959 | ## 11-01-2022 960 | 961 | main_author|title|update_date|publish_date 962 | ---|---|---|--- 963 | Sheraz Ahmed|[ExAID: A Multimodal Explanation Framework for Computer-Aided Diagnosis of Skin Lesions](http://arxiv.org/abs/2201.01249v1)|2022-01-04 17:11:28+00:00|04-01-2022 964 | 965 | ## 06-01-2022 966 | 967 | main_author|title|update_date|publish_date 968 | ---|---|---|--- 969 | Sheraz Ahmed|[ExAID: A Multimodal Explanation Framework for Computer-Aided Diagnosis of Skin Lesions](http://arxiv.org/abs/2201.01249v1)|2022-01-04 17:11:28+00:00|04-01-2022 970 | 971 | ## 04-01-2022 972 | 973 | main_author|title|update_date|publish_date 974 | ---|---|---|--- 975 | Bo Liu|[A Critical Review of Inductive Logic Programming Techniques for Explainable AI](http://arxiv.org/abs/2112.15319v1)|2021-12-31 06:34:32+00:00|31-12-2021 976 | Kevin W. Bowyer|[Gendered Differences in Face Recognition Accuracy Explained by Hairstyles, Makeup, and Facial Morphology](http://arxiv.org/abs/2112.14656v1)|2021-12-29 17:07:33+00:00|29-12-2021 977 | Peter Flach|[Explainability Is in the Mind of the Beholder: Establishing the Foundations of Explainable Artificial Intelligence](http://arxiv.org/abs/2112.14466v1)|2021-12-29 09:21:33+00:00|29-12-2021 978 | Hanwang Zhang|[Cross-Domain Empirical Risk Minimization for Unbiased Long-tailed Classification](http://arxiv.org/abs/2112.14380v1)|2021-12-29 03:18:47+00:00|29-12-2021 979 | Irfan Khan|[Explainable Signature-based Machine Learning Approach for Identification of Faults in Grid-Connected Photovoltaic Systems](http://arxiv.org/abs/2112.14842v1)|2021-12-25 15:11:18+00:00|25-12-2021 980 | Wulong Liu|[A Survey on Interpretable Reinforcement Learning](http://arxiv.org/abs/2112.13112v1)|2021-12-24 17:26:57+00:00|24-12-2021 981 | 982 | ## 28-12-2021 983 | 984 | main_author|title|update_date|publish_date 985 | ---|---|---|--- 986 | Yamisleydi Salgueiro|[Forward Composition Propagation for Explainable Neural Reasoning](http://arxiv.org/abs/2112.12717v1)|2021-12-23 17:10:11+00:00|23-12-2021 987 | May D. Wang|[Explainable Artificial Intelligence Methods in Combating Pandemics: A Systematic Review](http://arxiv.org/abs/2112.12705v2)|2021-12-25 05:06:58+00:00|23-12-2021 988 | Krishnaram Kenthapadi|[More Than Words: Towards Better Quality Interpretations of Text Classifiers](http://arxiv.org/abs/2112.12444v1)|2021-12-23 10:18:50+00:00|23-12-2021 989 | Georgios Kaissis|[Distributed Machine Learning and the Semblance of Trust](http://arxiv.org/abs/2112.11040v1)|2021-12-21 08:44:05+00:00|21-12-2021 990 | K. Weber|[Scope and Sense of Explainability for AI-Systems](http://arxiv.org/abs/2112.10551v2)|2021-12-22 14:18:33+00:00|20-12-2021 991 | Miroslaw Staron|[Towards Trustworthy Cross-patient Model Development](http://arxiv.org/abs/2112.10441v1)|2021-12-20 10:51:04+00:00|20-12-2021 992 | Yunan Zhang|[Unifying Model Explainability and Robustness for Joint Text Classification and Rationale Extraction](http://arxiv.org/abs/2112.10424v1)|2021-12-20 09:48:32+00:00|20-12-2021 993 | 994 | ## 21-12-2021 995 | 996 | main_author|title|update_date|publish_date 997 | ---|---|---|--- 998 | Graham Neubig|[Explain, Edit, and Understand: Rethinking User Study Design for Evaluating Model Explanations](http://arxiv.org/abs/2112.09669v1)|2021-12-17 18:29:56+00:00|17-12-2021 999 | Volker Tresp|[TLogic: Temporal Logical Rules for Explainable Link Forecasting on Temporal Knowledge Graphs](http://arxiv.org/abs/2112.08025v1)|2021-12-15 10:46:35+00:00|15-12-2021 1000 | Aasim Zafar|[Utilizing XAI technique to improve autoencoder based model for computer network anomaly detection with shapley additive explanation(SHAP)](http://arxiv.org/abs/2112.08442v1)|2021-12-14 09:42:04+00:00|14-12-2021 1001 | Ambreen Hanif|[Towards Explainable Artificial Intelligence in Banking and Financial Services](http://arxiv.org/abs/2112.08441v1)|2021-12-14 08:02:13+00:00|14-12-2021 1002 | Seong-Whan Lee|[Interpretable Convolutional Neural Networks for Subject-Independent Motor Imagery Classification](http://arxiv.org/abs/2112.07208v1)|2021-12-14 07:35:52+00:00|14-12-2021 1003 | Roberto Cipolla|[Discrete neural representations for explainable anomaly detection](http://arxiv.org/abs/2112.05585v1)|2021-12-10 14:56:58+00:00|10-12-2021 1004 | Julian McAuley|[Self-Supervised Bot Play for Conversational Recommendation with Justifications](http://arxiv.org/abs/2112.05197v1)|2021-12-09 20:07:41+00:00|09-12-2021 1005 | Naser Damer|[Explainability of the Implications of Supervised and Unsupervised Face Image Quality Estimations Through Activation Map Variation Analyses in Face Recognition Models](http://arxiv.org/abs/2112.04827v1)|2021-12-09 10:52:36+00:00|09-12-2021 1006 | Sergey Levine|[DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization](http://arxiv.org/abs/2112.04716v1)|2021-12-09 06:01:01+00:00|09-12-2021 1007 | Felix Hill|[Tell me why! -- Explanations support learning of relational and causal structure](http://arxiv.org/abs/2112.03753v2)|2021-12-08 12:48:22+00:00|07-12-2021 1008 | Jacob Andreas|[Quantifying Adaptability in Pre-trained Language Models with 500 Tasks](http://arxiv.org/abs/2112.03204v1)|2021-12-06 18:00:25+00:00|06-12-2021 1009 | Nithin Nagaraj|[Learning Generalized Causal Structure in Time-series](http://arxiv.org/abs/2112.03085v1)|2021-12-06 14:48:13+00:00|06-12-2021 1010 | Nicolas Papernot|[When the Curious Abandon Honesty: Federated Learning Is Not Private](http://arxiv.org/abs/2112.02918v1)|2021-12-06 10:37:03+00:00|06-12-2021 1011 | Zhengming Ding|[PSI: A Pedestrian Behavior Dataset for Socially Intelligent Autonomous Car](http://arxiv.org/abs/2112.02604v1)|2021-12-05 15:54:57+00:00|05-12-2021 1012 | Cheekong Lee|[ProtGNN: Towards Self-Explaining Graph Neural Networks](http://arxiv.org/abs/2112.00911v1)|2021-12-02 01:16:29+00:00|02-12-2021 1013 | Qinghua Hu|[Interactive Model with Structural Loss for Language-based Abductive Reasoning](http://arxiv.org/abs/2112.00284v1)|2021-12-01 05:21:07+00:00|01-12-2021 1014 | Hari Prasad Timmapathini|[Wiki to Automotive: Understanding the Distribution Shift and its impact on Named Entity Recognition](http://arxiv.org/abs/2112.00283v1)|2021-12-01 05:13:47+00:00|01-12-2021 1015 | 1016 | ## 14-12-2021 1017 | 1018 | main_author|title|update_date|publish_date 1019 | ---|---|---|--- 1020 | Neeraj Kumar|[Decoding the Protein-ligand Interactions Using Parallel Graph Neural Networks](http://arxiv.org/abs/2111.15144v1)|2021-11-30 06:02:04+00:00|30-11-2021 1021 | Alexander Wong|[TinyDefectNet: Highly Compact Deep Neural Network Architecture for High-Throughput Manufacturing Visual Quality Inspection](http://arxiv.org/abs/2111.14319v1)|2021-11-29 04:19:28+00:00|29-11-2021 1022 | Oliver Niggemann|[Learning Physical Concepts in Cyber-Physical Systems: A Case Study](http://arxiv.org/abs/2111.14151v1)|2021-11-28 14:24:52+00:00|28-11-2021 1023 | 1024 | ## 07-12-2021 1025 | 1026 | main_author|title|update_date|publish_date 1027 | ---|---|---|--- 1028 | Neeraj Kumar|[Decoding the Protein-ligand Interactions Using Parallel Graph Neural Networks](http://arxiv.org/abs/2111.15144v1)|2021-11-30 06:02:04+00:00|30-11-2021 1029 | Alexander Wong|[TinyDefectNet: Highly Compact Deep Neural Network Architecture for High-Throughput Manufacturing Visual Quality Inspection](http://arxiv.org/abs/2111.14319v1)|2021-11-29 04:19:28+00:00|29-11-2021 1030 | Oliver Niggemann|[Learning Physical Concepts in Cyber-Physical Systems: A Case Study](http://arxiv.org/abs/2111.14151v1)|2021-11-28 14:24:52+00:00|28-11-2021 1031 | 1032 | ## 02-12-2021 1033 | 1034 | main_author|title|update_date|publish_date 1035 | ---|---|---|--- 1036 | Neeraj Kumar|[Decoding the Protein-ligand Interactions Using Parallel Graph Neural Networks](http://arxiv.org/abs/2111.15144v1)|2021-11-30 06:02:04+00:00|30-11-2021 1037 | Alexander Wong|[TinyDefectNet: Highly Compact Deep Neural Network Architecture for High-Throughput Manufacturing Visual Quality Inspection](http://arxiv.org/abs/2111.14319v1)|2021-11-29 04:19:28+00:00|29-11-2021 1038 | Oliver Niggemann|[Learning Physical Concepts in Cyber-Physical Systems: A Case Study](http://arxiv.org/abs/2111.14151v1)|2021-11-28 14:24:52+00:00|28-11-2021 1039 | 1040 | ## 30-11-2021 1041 | 1042 | main_author|title|update_date|publish_date 1043 | ---|---|---|--- 1044 | Pablo Márquez-Neila|[Data Invariants to Understand Unsupervised Out-of-Distribution Detection](http://arxiv.org/abs/2111.13362v1)|2021-11-26 08:42:56+00:00|26-11-2021 1045 | Ruibin Bai|[One-shot Visual Reasoning on RPMs with an Application to Video Frame Prediction](http://arxiv.org/abs/2111.12301v1)|2021-11-24 06:51:38+00:00|24-11-2021 1046 | Fosca Giannotti|[Explainable Deep Image Classifiers for Skin Lesion Diagnosis](http://arxiv.org/abs/2111.11863v1)|2021-11-22 10:42:20+00:00|22-11-2021 1047 | Eliseo Papa|[Explainable Biomedical Recommendations via Reinforcement Learning Reasoning on Knowledge Graphs](http://arxiv.org/abs/2111.10625v1)|2021-11-20 16:41:34+00:00|20-11-2021 1048 | 1049 | ## 23-11-2021 1050 | 1051 | title|publish_date|main_author 1052 | ---|---|--- 1053 | No papers found this week|23-11-2021| 1054 | 1055 | ## 18-11-2021 1056 | 1057 | main_author|title|update_date|publish_date 1058 | ---|---|---|--- 1059 | Milo M. Lin|[Deep Distilling: automated code generation using explainable deep learning](http://arxiv.org/abs/2111.08275v1)|2021-11-16 07:45:41+00:00|16-11-2021 1060 | Przemysław Biecek|[LIMEcraft: Handcrafted superpixel selection and inspection for Visual eXplanations](http://arxiv.org/abs/2111.08094v1)|2021-11-15 21:40:34+00:00|15-11-2021 1061 | Rob J Hyndman|[LoMEF: A Framework to Produce Local Explanations for Global Model Time Series Forecasts](http://arxiv.org/abs/2111.07001v1)|2021-11-13 00:17:52+00:00|13-11-2021 1062 | Quanshi Zhang|[Discovering and Explaining the Representation Bottleneck of DNNs](http://arxiv.org/abs/2111.06236v1)|2021-11-11 14:35:20+00:00|11-11-2021 1063 | JianYu Shi|[STNN-DDI: A Substructure-aware Tensor Neural Network to Predict Drug-Drug Interactions](http://arxiv.org/abs/2111.05708v1)|2021-11-10 14:32:42+00:00|10-11-2021 1064 | Axel-Cyrille Ngonga Ngomo|[EvoLearner: Learning Description Logics with Evolutionary Algorithms](http://arxiv.org/abs/2111.04879v1)|2021-11-08 23:47:39+00:00|08-11-2021 1065 | Wael Abd-Almageed|[Explaining Face Presentation Attack Detection Using Natural Language](http://arxiv.org/abs/2111.04862v1)|2021-11-08 22:55:55+00:00|08-11-2021 1066 | Bernd Bischl|[Explaining Hyperparameter Optimization via Partial Dependence Plots](http://arxiv.org/abs/2111.04820v1)|2021-11-08 20:51:54+00:00|08-11-2021 1067 | Xia Hu|[Defense Against Explanation Manipulation](http://arxiv.org/abs/2111.04303v1)|2021-11-08 07:18:34+00:00|08-11-2021 1068 | MD. Golam Rabiul Alam|[Demystifying Deep Learning Models for Retinal OCT Disease Classification using Explainable AI](http://arxiv.org/abs/2111.03890v1)|2021-11-06 13:54:07+00:00|06-11-2021 1069 | 1070 | ## 16-11-2021 1071 | 1072 | title|publish_date|main_author 1073 | ---|---|--- 1074 | No papers found this week|09-11-2021| 1075 | 1076 | ## 09-11-2021 1077 | 1078 | title|publish_date|main_author 1079 | ---|---|--- 1080 | No papers found this week|09-11-2021| 1081 | 1082 | ## 09-11-2021 1083 | 1084 | main_author|title|update_date|publish_date 1085 | ---|---|---|--- 1086 | Rafael Chaves|[Causal inference with imperfect instrumental variables](http://arxiv.org/abs/2111.03029v1)|2021-11-04 17:34:27+00:00|04-11-2021 1087 | Nico Pfeifer|[Convolutional Motif Kernel Networks](http://arxiv.org/abs/2111.02272v1)|2021-11-03 15:06:09+00:00|03-11-2021 1088 | Timothy Hosgood|[Deep neural networks as nested dynamical systems](http://arxiv.org/abs/2111.01297v1)|2021-11-01 23:37:54+00:00|01-11-2021 1089 | Keith Butler|[Interpretable and Explainable Machine Learning for Materials Science and Chemistry](http://arxiv.org/abs/2111.01037v2)|2021-11-03 17:04:13+00:00|01-11-2021 1090 | Keyvan Ansari|[Explainable Artificial Intelligence for Smart City Application: A Secure and Trusted Platform](http://arxiv.org/abs/2111.00601v1)|2021-10-31 21:47:12+00:00|31-10-2021 1091 | 1092 | ## 02-11-2021 1093 | 1094 | main_author|title|update_date|publish_date 1095 | ---|---|---|--- 1096 | Jian Sun|[Path-Enhanced Multi-Relational Question Answering with Knowledge Graph Embeddings](http://arxiv.org/abs/2110.15622v1)|2021-10-29 08:37:46+00:00|29-10-2021 1097 | Chuang Gan|[Dynamic Visual Reasoning by Learning Differentiable Physics Models from Video and Language](http://arxiv.org/abs/2110.15358v1)|2021-10-28 17:59:13+00:00|28-10-2021 1098 | Anna Goldenberg|[Extracting Clinician's Goals by What-if Interpretable Modeling](http://arxiv.org/abs/2110.15165v1)|2021-10-28 14:41:06+00:00|28-10-2021 1099 | Mark Richardson|[A recursive robust filtering approach for 3D registration](http://arxiv.org/abs/2110.14932v1)|2021-10-28 07:50:02+00:00|28-10-2021 1100 | Tommi S. Jaakkola|[Understanding Interlocking Dynamics of Cooperative Rationalization](http://arxiv.org/abs/2110.13880v1)|2021-10-26 17:39:18+00:00|26-10-2021 1101 | Alexandre Mathieu|[Partial order: Finding Consensus among Uncertain Feature Attributions](http://arxiv.org/abs/2110.13369v1)|2021-10-26 02:53:14+00:00|26-10-2021 1102 | 1103 | ## 27-10-2021 1104 | 1105 | main_author|title|update_date|publish_date 1106 | ---|---|---|--- 1107 | Ewa Kijak|[Generating artificial texts as substitution or complement of training data](http://arxiv.org/abs/2110.13016v1)|2021-10-25 14:53:42+00:00|25-10-2021 1108 | Ila Fiete|[Map Induction: Compositional spatial submap learning for efficient exploration in novel environments](http://arxiv.org/abs/2110.12301v1)|2021-10-23 21:23:04+00:00|23-10-2021 1109 | 1110 | ## 26-10-2021 1111 | 1112 | main_author|title|update_date|publish_date 1113 | ---|---|---|--- 1114 | Gregory Ditzler|[ProtoShotXAI: Using Prototypical Few-Shot Architecture for Explainable AI](http://arxiv.org/abs/2110.11597v1)|2021-10-22 05:24:52+00:00|22-10-2021 1115 | Refael Vivanti|[Can Q-learning solve Multi Armed Bantids?](http://arxiv.org/abs/2110.10934v1)|2021-10-21 07:08:30+00:00|21-10-2021 1116 | Shane Legg|[Shaking the foundations: delusions in sequence models for interaction and control](http://arxiv.org/abs/2110.10819v1)|2021-10-20 23:31:05+00:00|20-10-2021 1117 | Boaz Lernerand Aharon Bar-Hillel|[Inference Graphs for CNN Interpretation](http://arxiv.org/abs/2110.10568v1)|2021-10-20 13:56:09+00:00|20-10-2021 1118 | Fabio Roli|[Fingerprint recognition with embedded presentation attacks detection: are we ready?](http://arxiv.org/abs/2110.10567v1)|2021-10-20 13:53:16+00:00|20-10-2021 1119 | Vassilis Christophides|[On Predictive Explanation of Data Anomalies](http://arxiv.org/abs/2110.09467v1)|2021-10-18 16:59:28+00:00|18-10-2021 1120 | Justin Carpentier|[Differentiable Rendering with Perturbed Optimizers](http://arxiv.org/abs/2110.09107v1)|2021-10-18 08:56:23+00:00|18-10-2021 1121 | Soeren Auer|[Ranking Facts for Explaining Answers to Elementary Science Questions](http://arxiv.org/abs/2110.09036v1)|2021-10-18 06:15:11+00:00|18-10-2021 1122 | Andreas Nürnberger|[TorchEsegeta: Framework for Interpretability and Explainability of Image-based Deep Learning Models](http://arxiv.org/abs/2110.08429v1)|2021-10-16 01:00:15+00:00|16-10-2021 1123 | Shuyi Lin|[COVID-19 Detection in Chest X-ray Images Using Swin-Transformer and Transformer in Transformer](http://arxiv.org/abs/2110.08427v1)|2021-10-16 00:53:21+00:00|16-10-2021 1124 | Michael White|[Towards Transparent Interactive Semantic Parsing via Step-by-Step Correction](http://arxiv.org/abs/2110.08345v1)|2021-10-15 20:11:22+00:00|15-10-2021 1125 | Yicong Yu|[Explainable Student Performance Prediction With Personalized Attention for Explaining Why A Student Fails](http://arxiv.org/abs/2110.08268v1)|2021-10-15 08:45:43+00:00|15-10-2021 1126 | Yejin Choi|[Delphi: Towards Machine Ethics and Norms](http://arxiv.org/abs/2110.07574v1)|2021-10-14 17:38:12+00:00|14-10-2021 1127 | Samuel Labi|[Development and testing of an image transformer for explainable autonomous driving systems](http://arxiv.org/abs/2110.05559v1)|2021-10-11 19:01:41+00:00|11-10-2021 1128 | Samuel Labi|[Reason induced visual attention for explainable autonomous driving](http://arxiv.org/abs/2110.07380v1)|2021-10-11 18:50:41+00:00|11-10-2021 1129 | Anderson Rocha|[Explainable Fact-checking through Question Answering](http://arxiv.org/abs/2110.05369v1)|2021-10-11 15:55:11+00:00|11-10-2021 1130 | Tobias Friedrich|[Towards Explainable Real Estate Valuation via Evolutionary Algorithms](http://arxiv.org/abs/2110.05116v1)|2021-10-11 09:51:18+00:00|11-10-2021 1131 | 1132 | ## 19-10-2021 1133 | 1134 | title|publish_date|main_author 1135 | ---|---|--- 1136 | No papers found this week|12-10-2021| 1137 | 1138 | ## 12-10-2021 1139 | 1140 | title|publish_date|main_author 1141 | ---|---|--- 1142 | No papers found this week|12-10-2021| 1143 | 1144 | ## 12-10-2021 1145 | 1146 | main_author|title|update_date|publish_date 1147 | ---|---|---|--- 1148 | Sangdoo Yun|[Which Shortcut Cues Will DNNs Choose? A Study from the Parameter-Space Perspective](http://arxiv.org/abs/2110.03095v1)|2021-10-06 22:51:26+00:00|06-10-2021 1149 | Anh Nguyen|[Coarse-to-Fine Reasoning for Visual Question Answering](http://arxiv.org/abs/2110.02526v1)|2021-10-06 06:29:52+00:00|06-10-2021 1150 | Bowen Zhou|[Trustworthy AI: From Principles to Practices](http://arxiv.org/abs/2110.01167v1)|2021-10-04 03:20:39+00:00|04-10-2021 1151 | Tim Menzies|[xFAIR: Better Fairness via Model-based Rebalancing of Protected Attributes](http://arxiv.org/abs/2110.01109v1)|2021-10-03 22:10:14+00:00|03-10-2021 1152 | Ala-Al-Fuqaha|[Explainable Event Recognition](http://arxiv.org/abs/2110.00755v1)|2021-10-02 08:40:33+00:00|02-10-2021 1153 | 1154 | ## 05-10-2021 1155 | 1156 | main_author|title|update_date|publish_date 1157 | ---|---|---|--- 1158 | Hamed Pirsiavash|[Consistent Explanations by Contrastive Learning](http://arxiv.org/abs/2110.00527v1)|2021-10-01 16:49:16+00:00|01-10-2021 1159 | Reginald E. Bryant|[An Empirical Study of Accuracy, Fairness, Explainability, Distributional Robustness, and Adversarial Robustness](http://arxiv.org/abs/2109.14653v1)|2021-09-29 18:21:19+00:00|29-09-2021 1160 | Joshua Tenenbaum|[Identity-Expression Ambiguity in 3D Morphable Face Models](http://arxiv.org/abs/2109.14203v1)|2021-09-29 06:11:43+00:00|29-09-2021 1161 | L Azizi|[Non-stationary Gaussian process discriminant analysis with variable selection for high-dimensional functional data](http://arxiv.org/abs/2109.14171v1)|2021-09-29 03:35:49+00:00|29-09-2021 1162 | 1163 | ## 29-09-2021 1164 | 1165 | main_author|title|update_date|publish_date 1166 | ---|---|---|--- 1167 | Sunil Reddy Tiyyagura|[DeepPSL: End-to-end perception and reasoning with applications to zero shot learning](http://arxiv.org/abs/2109.13662v1)|2021-09-28 12:30:33+00:00|28-09-2021 1168 | Daniel A. Keim|[Time Series Model Attribution Visualizations as Explanations](http://arxiv.org/abs/2109.12935v1)|2021-09-27 10:44:07+00:00|27-09-2021 1169 | 1170 | ## 28-09-2021 1171 | 1172 | main_author|title|update_date|publish_date 1173 | ---|---|---|--- 1174 | Benjamin I. P. Rubinstein|[Local Intrinsic Dimensionality Signals Adversarial Perturbations](http://arxiv.org/abs/2109.11803v1)|2021-09-24 08:29:50+00:00|24-09-2021 1175 | Changyou Chen|[AES Are Both Overstable And Oversensitive: Explaining Why And Proposing Defenses](http://arxiv.org/abs/2109.11728v1)|2021-09-24 03:49:38+00:00|24-09-2021 1176 | 1177 | ## 23-09-2021 1178 | 1179 | main_author|title|update_date|publish_date 1180 | ---|---|---|--- 1181 | Gabriel Loaiza-Ganem|[Entropic Issues in Likelihood-Based OOD Detection](http://arxiv.org/abs/2109.10794v1)|2021-09-22 15:32:57+00:00|22-09-2021 1182 | Alex Pentland|[Investigating and Modeling the Dynamics of Long Ties](http://arxiv.org/abs/2109.10523v1)|2021-09-22 05:40:45+00:00|22-09-2021 1183 | Wenyuan Xu|[FakeWake: Understanding and Mitigating Fake Wake-up Words of Voice Assistants](http://arxiv.org/abs/2109.09958v1)|2021-09-21 04:46:08+00:00|21-09-2021 1184 | Luis Martí-Bonmatí|[FUTURE-AI: Guiding Principles and Consensus Recommendations for Trustworthy Artificial Intelligence in Future Medical Imaging](http://arxiv.org/abs/2109.09658v2)|2021-09-21 07:42:01+00:00|20-09-2021 1185 | Michael Färber|[Explaining Convolutional Neural Networks by Tagging Filters](http://arxiv.org/abs/2109.09389v1)|2021-09-20 09:27:27+00:00|20-09-2021 1186 | Mohammad Rashedul Hasan|[A Study of the Generalizability of Self-Supervised Representations](http://arxiv.org/abs/2109.09150v1)|2021-09-19 15:57:37+00:00|19-09-2021 1187 | Lili Mou|[Weakly Supervised Explainable Phrasal Reasoning with Neural Fuzzy Logic](http://arxiv.org/abs/2109.08927v1)|2021-09-18 13:04:23+00:00|18-09-2021 1188 | Yun-Nung Chen|[Relating Neural Text Degeneration to Exposure Bias](http://arxiv.org/abs/2109.08705v1)|2021-09-17 18:11:03+00:00|17-09-2021 1189 | 1190 | ## 21-09-2021 1191 | 1192 | main_author|title|update_date|publish_date 1193 | ---|---|---|--- 1194 | Ngoc Thang Vu|[Does External Knowledge Help Explainable Natural Language Inference? Automatic Evaluation vs. Human Ratings](http://arxiv.org/abs/2109.07833v1)|2021-09-16 09:56:20+00:00|16-09-2021 1195 | Mohsen Guizani|[Internet of Behavior (IoB) and Explainable AI Systems for Influencing IoT Behavior](http://arxiv.org/abs/2109.07239v1)|2021-09-15 12:16:11+00:00|15-09-2021 1196 | Dimitris Askounis|[Explainable Identification of Dementia from Transcripts using Transformer Networks](http://arxiv.org/abs/2109.06980v1)|2021-09-14 21:49:05+00:00|14-09-2021 1197 | Ulises Cortés|[A trainable monogenic ConvNet layer robust in front of large contrast changes in image classification](http://arxiv.org/abs/2109.06926v1)|2021-09-14 18:50:07+00:00|14-09-2021 1198 | Alexander Wong|[COVID-Net Clinical ICU: Enhanced Prediction of ICU Admission for COVID-19 Patients via Explainability and Trust Quantification](http://arxiv.org/abs/2109.06711v1)|2021-09-14 14:16:32+00:00|14-09-2021 1199 | Joachim Denzler|[Anomaly Attribution of Multivariate Time Series using Counterfactual Reasoning](http://arxiv.org/abs/2109.06562v1)|2021-09-14 10:15:52+00:00|14-09-2021 1200 | Diyi Yang|[Latent Hatred: A Benchmark for Understanding Implicit Hate Speech](http://arxiv.org/abs/2109.05322v1)|2021-09-11 16:52:56+00:00|11-09-2021 1201 | 1202 | ## 14-09-2021 1203 | 1204 | main_author|title|update_date|publish_date 1205 | ---|---|---|--- 1206 | Kun He|[TimeTraveler: Reinforcement Learning for Temporal Knowledge Graph Forecasting](http://arxiv.org/abs/2109.04101v1)|2021-09-09 08:41:01+00:00|09-09-2021 1207 | Sarem Seitz|[Self-explaining variational posterior distributions for Gaussian Process models](http://arxiv.org/abs/2109.03708v1)|2021-09-08 15:14:22+00:00|08-09-2021 1208 | Wai Lam|[Exploiting Reasoning Chains for Multi-hop Science Question Answering](http://arxiv.org/abs/2109.02905v1)|2021-09-07 07:22:07+00:00|07-09-2021 1209 | Bin Yang|[Estimation of Bivariate Structural Causal Models by Variational Gaussian Process Regression Under Likelihoods Parametrised by Normalising Flows](http://arxiv.org/abs/2109.02521v1)|2021-09-06 14:52:58+00:00|06-09-2021 1210 | Yongfeng Zhang|[Counterfactual Evaluation for Explainable AI](http://arxiv.org/abs/2109.01962v1)|2021-09-05 01:38:49+00:00|05-09-2021 1211 | 1212 | ## 07-09-2021 1213 | 1214 | main_author|title|update_date|publish_date 1215 | ---|---|---|--- 1216 | Marshall Burke|[Wildfire smoke plume segmentation using geostationary satellite imagery](http://arxiv.org/abs/2109.01637v1)|2021-09-03 17:29:58+00:00|03-09-2021 1217 | Song-Chun Zhu|[CX-ToM: Counterfactual Explanations with Theory-of-Mind for Enhancing Human Trust in Image Recognition Models](http://arxiv.org/abs/2109.01401v2)|2021-09-06 07:00:34+00:00|03-09-2021 1218 | Ibrahim Habli|[The Role of Explainability in Assuring Safety of Machine Learning in Healthcare](http://arxiv.org/abs/2109.00520v1)|2021-09-01 09:32:14+00:00|01-09-2021 1219 | William Yang Wang|[FinQA: A Dataset of Numerical Reasoning over Financial Data](http://arxiv.org/abs/2109.00122v1)|2021-09-01 00:08:14+00:00|01-09-2021 1220 | Meiqing Wang|[Chi-square Loss for Softmax: an Echo of Neural Network Structure](http://arxiv.org/abs/2108.13822v1)|2021-08-31 13:28:25+00:00|31-08-2021 1221 | 1222 | ## 31-08-2021 1223 | 1224 | title|publish_date|main_author 1225 | ---|---|--- 1226 | No papers found this week|31-08-2021| 1227 | 1228 | ## 30-08-2021 1229 | 1230 | main_author|title|update_date|publish_date 1231 | ---|---|---|--- 1232 | Andreas Holzinger|[Network Module Detection from Multi-Modal Node Features with a Greedy Decision Forest for Actionable Explainable AI](http://arxiv.org/abs/2108.11674v1)|2021-08-26 09:42:44+00:00|26-08-2021 1233 | Bartosz Zieliński|[ProtoMIL: Multiple Instance Learning with Prototypical Parts for Fine-Grained Interpretability](http://arxiv.org/abs/2108.10612v1)|2021-08-24 10:02:31+00:00|24-08-2021 1234 | Yongfeng Zhang|[Counterfactual Explainable Recommendation](http://arxiv.org/abs/2108.10539v1)|2021-08-24 06:37:57+00:00|24-08-2021 1235 | Heung-Il Suk|[Learn-Explain-Reinforce: Counterfactual Reasoning and Its Guidance to Reinforce an Alzheimer's Disease Diagnosis Model](http://arxiv.org/abs/2108.09451v1)|2021-08-21 07:29:13+00:00|21-08-2021 1236 | Pedro A. Moreno-Sanchez|[Improvement of a Prediction Model for Heart Failure Survival through Explainable Artificial Intelligence](http://arxiv.org/abs/2108.10717v1)|2021-08-20 09:03:26+00:00|20-08-2021 1237 | 1238 | ## 24-08-2021 1239 | 1240 | main_author|title|update_date|publish_date 1241 | ---|---|---|--- 1242 | Shuang Mei|[Diffeomorphic Particle Image Velocimetry](http://arxiv.org/abs/2108.07438v1)|2021-08-17 04:26:09+00:00|17-08-2021 1243 | Filippo Maria Bianchi|[Detecting and interpreting faults in vulnerable power grids with machine learning](http://arxiv.org/abs/2108.07060v1)|2021-08-16 12:54:36+00:00|16-08-2021 1244 | Thomas Serre|[Understanding the computational demands underlying visual reasoning](http://arxiv.org/abs/2108.03603v1)|2021-08-08 10:46:53+00:00|08-08-2021 1245 | Bing Xiang|[Dual Reader-Parser on Hybrid Textual and Tabular Evidence for Open Domain Question Answering](http://arxiv.org/abs/2108.02866v1)|2021-08-05 22:04:13+00:00|05-08-2021 1246 | Hendrik Lens|[An Interpretable Probabilistic Model for Short-Term Solar Power Forecasting Using Natural Gradient Boosting](http://arxiv.org/abs/2108.04058v1)|2021-08-05 12:59:38+00:00|05-08-2021 1247 | Jia Li|[Mixture of Linear Models Co-supervised by Deep Neural Networks](http://arxiv.org/abs/2108.04035v1)|2021-08-05 02:08:35+00:00|05-08-2021 1248 | Tom Goldstein|[Where do Models go Wrong? Parameter-Space Saliency Maps for Explainability](http://arxiv.org/abs/2108.01335v1)|2021-08-03 07:32:34+00:00|03-08-2021 1249 | Keyur Faldu|[Knowledge-intensive Language Understanding for Explainable AI](http://arxiv.org/abs/2108.01174v1)|2021-08-02 21:12:30+00:00|02-08-2021 1250 | Mehdi Moradi|[Chest ImaGenome Dataset for Clinical Reasoning](http://arxiv.org/abs/2108.00316v1)|2021-07-31 20:10:30+00:00|31-07-2021 1251 | Ruwen Qin|[Towards explainable artificial intelligence (XAI) for early anticipation of traffic accidents](http://arxiv.org/abs/2108.00273v1)|2021-07-31 15:53:32+00:00|31-07-2021 1252 | Olfa Nasraoui|[Debiased Explainable Pairwise Ranking from Implicit Feedback](http://arxiv.org/abs/2107.14768v1)|2021-07-30 17:19:37+00:00|30-07-2021 1253 | Xin Wang|[ReFormer: The Relational Transformer for Image Captioning](http://arxiv.org/abs/2107.14178v1)|2021-07-29 17:03:36+00:00|29-07-2021 1254 | Nenghai Yu|[Abnormal Behavior Detection Based on Target Analysis](http://arxiv.org/abs/2107.13706v1)|2021-07-29 02:03:47+00:00|29-07-2021 1255 | Ronald X. Xu|[An explainable two-dimensional single model deep learning approach for Alzheimer's disease diagnosis and brain atrophy localization](http://arxiv.org/abs/2107.13200v1)|2021-07-28 07:19:00+00:00|28-07-2021 1256 | Razvan Pascanu|[On the Role of Optimization in Double Descent: A Least Squares Study](http://arxiv.org/abs/2107.12685v1)|2021-07-27 09:13:11+00:00|27-07-2021 1257 | Moreno Marzolla|[Dissecting FLOPs along input dimensions for GreenAI cost estimations](http://arxiv.org/abs/2107.11949v1)|2021-07-26 04:08:41+00:00|26-07-2021 1258 | Pietro Liò|[GCExplainer: Human-in-the-Loop Concept-based Explanations for Graph Neural Networks](http://arxiv.org/abs/2107.11889v1)|2021-07-25 20:52:48+00:00|25-07-2021 1259 | Gyumin Lim|[Unsupervised Detection of Adversarial Examples with Model Explanations](http://arxiv.org/abs/2107.10480v1)|2021-07-22 06:54:18+00:00|22-07-2021 1260 | Vitaly Shmatikov|[Spinning Sequence-to-Sequence Models with Meta-Backdoors](http://arxiv.org/abs/2107.10443v1)|2021-07-22 03:41:52+00:00|22-07-2021 1261 | Jeh-Kwang Ryu|[CogME: A Novel Evaluation Metric for Video Understanding Intelligence](http://arxiv.org/abs/2107.09847v1)|2021-07-21 02:33:37+00:00|21-07-2021 1262 | Mark T. Keane|[Uncertainty Estimation and Out-of-Distribution Detection for Counterfactual Explanations: Pitfalls and Solutions](http://arxiv.org/abs/2107.09734v1)|2021-07-20 19:09:10+00:00|20-07-2021 1263 | Daniel L. K. Yamins|[Rethinking the limiting dynamics of SGD: modified loss, phase space oscillations, and anomalous diffusion](http://arxiv.org/abs/2107.09133v1)|2021-07-19 20:18:57+00:00|19-07-2021 1264 | Toshiki Shibahara|[MEGEX: Data-Free Model Extraction Attack against Gradient-Based Explainable AI](http://arxiv.org/abs/2107.08909v1)|2021-07-19 14:25:06+00:00|19-07-2021 1265 | Catarina Moreira|[Explainable AI Enabled Inspection of Business Process Prediction Models](http://arxiv.org/abs/2107.09767v1)|2021-07-16 06:51:18+00:00|16-07-2021 1266 | Pietro Liò|[Algorithmic Concept-based Explainable Reasoning](http://arxiv.org/abs/2107.07493v1)|2021-07-15 17:44:51+00:00|15-07-2021 1267 | Cynthia Rudin|[Interpretable Mammographic Image Classification using Cased-Based Reasoning and Deep Learning](http://arxiv.org/abs/2107.05605v1)|2021-07-12 17:42:09+00:00|12-07-2021 1268 | Manoranjan Mohanty|[Explainable AI: current status and future directions](http://arxiv.org/abs/2107.07045v1)|2021-07-12 08:42:19+00:00|12-07-2021 1269 | Changsheng Xu|[DualVGR: A Dual-Visual Graph Reasoning Unit for Video Question Answering](http://arxiv.org/abs/2107.04768v1)|2021-07-10 06:08:15+00:00|10-07-2021 1270 | Quanshi Zhang|[Interpretable Compositional Convolutional Neural Networks](http://arxiv.org/abs/2107.04474v1)|2021-07-09 15:01:24+00:00|09-07-2021 1271 | Maikel Leon Espinosa|[Recurrence-Aware Long-Term Cognitive Network for Explainable Pattern Classification](http://arxiv.org/abs/2107.03423v1)|2021-07-07 18:14:50+00:00|07-07-2021 1272 | David Shih|[New Methods and Datasets for Group Anomaly Detection From Fundamental Physics](http://arxiv.org/abs/2107.02821v1)|2021-07-06 18:00:57+00:00|06-07-2021 1273 | Ronnie Alves|[Does Dataset Complexity Matters for Model Explainers?](http://arxiv.org/abs/2107.02661v1)|2021-07-06 15:01:04+00:00|06-07-2021 1274 | Deborah L. McGuinness|[Leveraging Clinical Context for User-Centered Explainability: A Diabetes Use Case](http://arxiv.org/abs/2107.02359v3)|2021-07-15 18:35:40+00:00|06-07-2021 1275 | Dimosthenis Kyriazis|[A Review of Explainable Artificial Intelligence in Manufacturing](http://arxiv.org/abs/2107.02295v1)|2021-07-05 21:59:55+00:00|05-07-2021 1276 | Michael C. Thrun|[An Explainable AI System for the Diagnosis of High Dimensional Biomedical Data](http://arxiv.org/abs/2107.01820v1)|2021-07-05 07:00:29+00:00|05-07-2021 1277 | Alice Gao|[COVID-VIT: Classification of COVID-19 from CT chest images based on vision transformer models](http://arxiv.org/abs/2107.01682v1)|2021-07-04 16:55:51+00:00|04-07-2021 1278 | Hamido Fujita|[Heterogeneous Graph Attention Network for Multi-hop Machine Reading Comprehension](http://arxiv.org/abs/2107.00841v1)|2021-07-02 05:29:39+00:00|02-07-2021 1279 | Quanyan Zhu|[Reinforcement Learning for Feedback-Enabled Cyber Resilience](http://arxiv.org/abs/2107.00783v1)|2021-07-02 01:08:45+00:00|02-07-2021 1280 | Artur d'Avila Garcez|[Contrastive Counterfactual Visual Explanations With Overdetermination](http://arxiv.org/abs/2106.14556v1)|2021-06-28 10:24:17+00:00|28-06-2021 1281 | Hisashi Kashima|[Crowdsourcing Evaluation of Saliency-based XAI Methods](http://arxiv.org/abs/2107.00456v1)|2021-06-27 17:37:53+00:00|27-06-2021 1282 | 1283 | -------------------------------------------------------------------------------- /mcmc/new_df.csv: -------------------------------------------------------------------------------- 1 | main_author|title|update_date|publish_date 2 | ---|---|---|--- 3 | Chao Chen|[Topology-Aware Uncertainty for Image Segmentation](http://arxiv.org/abs/2306.05671v1)|2023-06-09 05:01:55+00:00|09-06-2023 4 | Gregory W. Wornell|[SGLD-Based Information Criteria and the Over-Parameterized Regime](http://arxiv.org/abs/2306.05583v1)|2023-06-08 22:54:48+00:00|08-06-2023 5 | Le Sun|[ToolAlpaca: Generalized Tool Learning for Language Models with 3000 Simulated Cases](http://arxiv.org/abs/2306.05301v1)|2023-06-08 15:46:32+00:00|08-06-2023 6 | Shanghang Zhang|[ViDA: Homeostatic Visual Domain Adapter for Continual Test Time Adaptation](http://arxiv.org/abs/2306.04344v1)|2023-06-07 11:18:53+00:00|07-06-2023 7 | Ljubisa Bojic|[Personality testing of GPT-3: Limited temporal reliability, but highlighted social desirability of GPT-3's personality instruments results](http://arxiv.org/abs/2306.04308v1)|2023-06-07 10:14:17+00:00|07-06-2023 8 | Maarten De Vos|[U-PASS: an Uncertainty-guided deep learning Pipeline for Automated Sleep Staging](http://arxiv.org/abs/2306.04663v1)|2023-06-07 08:27:36+00:00|07-06-2023 9 | Tobias Sutter|[End-to-End Learning for Stochastic Optimization: A Bayesian Perspective](http://arxiv.org/abs/2306.04174v2)|2023-06-11 10:29:32+00:00|07-06-2023 10 | Anoop Cherian|[Active Sparse Conversations for Improved Audio-Visual Embodied Navigation](http://arxiv.org/abs/2306.04047v1)|2023-06-06 22:32:49+00:00|06-06-2023 11 | Bernhard Schölkopf|[Stochastic Marginal Likelihood Gradients using Neural Tangent Kernels](http://arxiv.org/abs/2306.03968v1)|2023-06-06 19:02:57+00:00|06-06-2023 12 | Goran Radanovic|[Sequential Principal-Agent Problems with Communication: Efficient Computation and Learning](http://arxiv.org/abs/2306.03832v1)|2023-06-06 16:20:44+00:00|06-06-2023 13 | Dawei Song|[A Survey of Quantum-Cognitively Inspired Sentiment Analysis Models](http://arxiv.org/abs/2306.03608v1)|2023-06-06 11:54:48+00:00|06-06-2023 14 | Yulan He|[CUE: An Uncertainty Interpretation Framework for Text Classifiers Built on Pre-Trained Language Models](http://arxiv.org/abs/2306.03598v1)|2023-06-06 11:37:46+00:00|06-06-2023 15 | Michael Hinczewski|[Machine learning in and out of equilibrium](http://arxiv.org/abs/2306.03521v1)|2023-06-06 09:12:49+00:00|06-06-2023 16 | Charles Patrick Martin|[Latent Optimal Paths by Gumbel Propagation for Variational Bayesian Dynamic Programming](http://arxiv.org/abs/2306.02568v1)|2023-06-05 03:47:59+00:00|05-06-2023 17 | Baskar Ganapathysubramanian|[Deep learning powered real-time identification of insects using citizen science data](http://arxiv.org/abs/2306.02507v1)|2023-06-04 23:56:53+00:00|04-06-2023 18 | Robert Gower|[Provable convergence guarantees for black-box variational inference](http://arxiv.org/abs/2306.03638v1)|2023-06-04 11:31:41+00:00|04-06-2023 19 | Ilias Bilionis|[An information field theory approach to Bayesian state and parameter estimation in dynamical systems](http://arxiv.org/abs/2306.02150v1)|2023-06-03 16:36:43+00:00|03-06-2023 20 | Arno Solin|[Variational Gaussian Process Diffusion Processes](http://arxiv.org/abs/2306.02066v1)|2023-06-03 09:43:59+00:00|03-06-2023 21 | Rose Yu|[DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting](http://arxiv.org/abs/2306.01984v1)|2023-06-03 02:46:31+00:00|03-06-2023 22 | --------------------------------------------------------------------------------