└── README.md /README.md: -------------------------------------------------------------------------------- 1 | ## Content 2 | - [Survey papers](https://github.com/xanhho/Reading-Comprehension-Question-Answering-Papers/blob/master/README.md#surveyoverview-papersdocuments-should-read-on-machine-reading-comprehension) 3 | - [Slides](https://github.com/xanhho/Reading-Comprehension-Question-Answering-Papers/blob/master/README.md#slides) 4 | - [Evaluation papers](https://github.com/xanhho/Reading-Comprehension-Question-Answering-Papers/blob/master/README.md#evaluation-papers) 5 | - [Models (for single-hop)](https://github.com/xanhho/Reading-Comprehension-Question-Answering-Papers/blob/master/README.md#basic-papersmodels) 6 | - [Knowledge-based Machine Reading Comprehension](https://github.com/xanhho/Reading-Comprehension-Question-Answering-Papers/blob/master/README.md#kbmrc-knowledge-based-machine-reading-comprehension) 7 | - [Open-domain Question Answering](https://github.com/xanhho/Reading-Comprehension-Question-Answering-Papers/blob/master/README.md#opqa-open-domain-question-answering) 8 | - [Unanswerable Questions](https://github.com/xanhho/Reading-Comprehension-Question-Answering-Papers/blob/master/README.md#uq-unanswerable-questions) 9 | - [Multi-Passage Machine Reading Comprehension](https://github.com/xanhho/Reading-Comprehension-Question-Answering-Papers/blob/master/README.md#multi-passage-mrc-multi-passage-machine-reading-comprehension) 10 | - [Conversational Question Answering](https://github.com/xanhho/Reading-Comprehension-Question-Answering-Papers/blob/master/README.md#cqa-conversational-question-answering) 11 | - [Datasets](https://github.com/xanhho/Reading-Comprehension-Question-Answering-Papers/blob/master/README.md#datasets) 12 | - [Datasets with Explanations](https://github.com/xanhho/Reading-Comprehension-Question-Answering-Papers/blob/master/README.md#datasets-with-explanations) 13 | - [QA over KG](https://github.com/xanhho/Reading-Comprehension-Question-Answering-Papers/blob/master/README.md#qa-over-kg) 14 | - [Question answering systems](https://github.com/xanhho/Reading-Comprehension-Question-Answering-Papers/blob/master/README.md#question-answering-systems) 15 | - [Knowledge bases/Knowledge sources](https://github.com/xanhho/Reading-Comprehension-Question-Answering-Papers/blob/master/README.md#knowledge-basesknowledge-sources) 16 | - [Papers misc](https://github.com/xanhho/Reading-Comprehension-Question-Answering-Papers/blob/master/README.md#others-misc-model-transfer-learning-data-augmentation-domain-adaption-cross-lingual-) 17 | 18 | 19 | ## Survey/Overview papers/documents should read on Machine Reading Comprehension 20 | - Fengbin Zhu et al., **Retrieving and Reading : A Comprehensive Survey on Open-domain Question Answering**, arXiv, 2021, [paper](https://arxiv.org/pdf/2101.00774.pdf) 21 | - Mokanarangan Thayaparan, Marco Valentino, and André Freitas, **A Survey on Explainability in Machine Reading Comprehension**, arXiv, 2020, [paper](https://arxiv.org/pdf/2010.00389.pdf) 22 | - Viktor Schlegel et al., **Beyond Leaderboards: A survey of methods for revealing weaknesses in Natural Language Inference data and models**, arXiv, 2020, [paper](https://arxiv.org/pdf/2005.14709.pdf) 23 | - Viktor Schlegel et al., **A Framework for Evaluation of Machine Reading Comprehension Gold Standards**, arXiv, 2020, [paper](https://arxiv.org/pdf/2003.04642.pdf) 24 | - Chengchang Zeng et al., **A Survey on Machine Reading Comprehension: Tasks, Evaluation Metrics, and Benchmark Datasets**, arXiv, 2020, [paper](https://arxiv.org/pdf/2006.11880.pdf). 25 | - Razieh Baradaran, Razieh Ghiasi, and Hossein Amirkhani, **A Survey on Machine Reading Comprehension Systems**, arXiv, 6 Jan 2020, [paper](https://arxiv.org/abs/2001.01582). 26 | - Matthew Gardner et al., **On Making Reading Comprehension More Comprehensive.**, aclweb, 2019, [paper](https://www.aclweb.org/anthology/D19-5815.pdf). 27 | - Shanshan Liu et al., **Neural Machine Reading Comprehension: Methods and Trends**, arXiv, 2019, [paper](https://arxiv.org/pdf/1907.01118.pdf). 28 | - Xin Zhang et al., **Machine Reading Comprehension: a Literature Review**, arXiv, 2019, [paper](https://arxiv.org/pdf/1907.01686.pdf). 29 | - Boyu Qiu et al., **A Survey on Neural Machine Reading Comprehension**, arXiv, 2019, [paper](https://arxiv.org/pdf/1906.03824.pdf). 30 | - Danqi Chen: **Neural Reading Comprehension and Beyond**. PhD thesis, Stanford University, 2018, [paper](https://github.com/danqi/thesis). 31 | 32 | 33 | ## Slides 34 | - Sebastian Riedel, Reading and Reasoning with Neural Program Interpreters, [slides](https://mrqa2018.github.io/slides/sebastian.pdf), MRQA 2018. 35 | - Phil Blunsom, Data driven reading comprehension: successes and limitations, [slides](https://mrqa2018.github.io/slides/phil.pdf), MRQA 2018. 36 | - Jianfeng Gao, Multi-step reasoning neural networks for question answering, [slides](https://mrqa2018.github.io/slides/jianfeng.pdf), MRQA 2018. 37 | - Sameer Singh, Questioning Question Answering Answers, [slides](https://mrqa2018.github.io/slides/sameer.pdf), MRQA 2018. 38 | 39 | 40 | ## Evaluation papers 41 | - Diana Galvan, **Active Reading Comprehension: A dataset for learning the Question-Answer Relationship strategy**, ACL 2019, [paper](https://www.aclweb.org/anthology/P19-2014). 42 | - Divyansh Kaushik and Zachary C. Lipton, **How Much Reading Does Reading Comprehension Require? A Critical Investigation of Popular Benchmarks**, EMNLP 2018, [paper](https://www.aclweb.org/anthology/D18-1546.pdf). 43 | - Saku Sugawara et al., **What Makes Reading Comprehension Questions Easier?**, EMNLP 2018, [paper](https://www.aclweb.org/anthology/D18-1453.pdf). 44 | - Pramod K. Mudrakarta et al., **Did the Model Understand the Question?**, ACL 2018, [paper](https://www.aclweb.org/anthology/P18-1176.pdf). 45 | - Robin Jia and Percy Liang, **Adversarial Examples for Evaluating Reading Comprehension Systems**, EMNLP 2017, [paper](https://www.aclweb.org/anthology/D17-1215.pdf). 46 | - Saku Sugawara et al., **Evaluation Metrics for Machine Reading Comprehension: Prerequisite Skills and Readability**, ACL 2017, [paper](https://www.aclweb.org/anthology/P17-1075.pdf). 47 | - Saku Sugawara et al., **Prerequisite Skills for Reading Comprehension: Multi-perspective Analysis of MCTest Datasets and Systems**, AAAI 2017, [paper](http://www.aaai.org/Conferences/AAAI/2017/PreliminaryPapers/14-Sugawara-14614.pdf). 48 | - Danqi Chen et al., **A Thorough Examination of the CNN/Daily Mail Reading Comprehension Task**, ACL 2016, [paper](https://www.aclweb.org/anthology/P16-1223.pdf). 49 | 50 | 51 | ## Basic Papers/Models 52 | | Year | Title | Model| Datasets | Misc | Paper, Source Code | 53 | | ------------- | ------------- | ------------- | ------------- | ------------- | ------------- | 54 | | 2019 | XLNet: Generalized Autoregressive Pretraining for Language Understanding | XLNet | Race, SQuAD 1.1, SQuAD 2.0 | pretrained LM | [paper](https://arxiv.org/pdf/1906.08237.pdf), [code](https://github.com/zihangdai/xlnet/) | 55 | | 2019 | BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding | BERT | GLUE, SQuAD 1.1, SQuAD 2.0, SWAG | pretrained LM | [paper](https://www.aclweb.org/anthology/N19-1423), [code](https://github.com/google-research/bert) | 56 | | 2018 | S-NET: From Answer Extraction to Answer Generation for Machine Reading Comprehension | S-NET | MS-MARCO | multiple passages | [paper](https://arxiv.org/pdf/1706.04815.pdf), [code]| 57 | | 2018 | QANET: Combining local Convolution with global Self-Attention for Reading Comprehension | QANet | SQuAD 1.1 | | [paper](https://openreview.net/pdf?id=B14TlG-RW), [code](https://github.com/google-research/google-research/tree/master/qanet) | 58 | | 2017 | ReasoNet: Learning to Stop Reading in Machine Comprehension | ReasoNet | CNN and Daily Mail, SQuAD 1.1 | | [paper](https://arxiv.org/pdf/1609.05284.pdf), [code] | 59 | | 2017 | Reading Wikipedia to Answer Open-Domain Questions | DrQA | Wikipedia, SQuAD 1.1, CuratedTREC, WebQuestions, WikiMovies | OPQA, Multi-Passage MRC | [paper](https://www.aclweb.org/anthology/P17-1171), [code](https://github.com/facebookresearch/DrQA) | 60 | | 2017 | R-Net: Machine Reading Comprehension with Self-Matching Networks | R-Net | SQuAD 1.1, MS-MARCO | | [paper](https://www.microsoft.com/en-us/research/wp-content/uploads/2017/05/r-net.pdf), [code](https://github.com/HKUST-KnowComp/R-Net) | 61 | | 2017 | Machine Comprehension Using Match-LSTM and Answer Pointer | Match-LSTM + Pointer Network| SQuAD 1.1 | | [paper](https://arxiv.org/pdf/1608.07905.pdf), [code](https://github.com/shuohangwang/SeqMatchSeq) | 62 | | 2017 | Gated-Attention Readers for Text Comprehension | Gated-attention Reader | CNN and Daily Mail, Children’s Book Test, Who Did What | | [paper](https://arxiv.org/pdf/1606.01549.pdf), [code](https://github.com/bdhingra/ga-reader) | 63 | | 2017 | Gated Self-Matching Networks for Reading Comprehension and Question Answering | Gated Self-Matching | SQuAD 1.1 | | [paper](https://www.aclweb.org/anthology/P17-1018.pdf), [code] | 64 | | 2017 | Dynamic CoAttention Networks for Question Answering | Dynamic coattention networks | SQuAD 1.1 | | [paper](https://arxiv.org/pdf/1611.01604.pdf), [code](https://github.com/thomasfermi/Dynamic-Coattention-Network-for-SQuAD) | 65 | | 2017 | DCN+: Mixed Objective and Deep Residual CoAttention for Question Answering | DCN+ | SQuAD 1.1 | | [paper](https://arxiv.org/pdf/1711.00106.pdf), [code](https://github.com/andrejonasson/dynamic-coattention-network-plus) | 66 | | 2017 | Bi-directional Attention Flow for Machine Comprehension | BiDAF | SQuAD 1.1 | | [paper](https://arxiv.org/pdf/1611.01603.pdf), [code](https://github.com/allenai/bi-att-flow) | 67 | | 2017 | Attention-over-Attention Neural Networks for Reading Comprehension | Attention-over-Attention Reader | Children’s Book Test, CNN and Daily Mail | | [paper](https://www.aclweb.org/anthology/P17-1055.pdf), [code](https://github.com/OlavHN/attention-over-attention)| 68 | | 2016 | Text Understanding with the Attention Sum Reader Network | Attention Sum Reader | Children’s Book Test, CNN and Daily Mail | | [paper](https://www.aclweb.org/anthology/P16-1086), [code](https://github.com/rkadlec/asreader) | 69 | | 2016 | Multi-Perspective Context Matching for Machine Comprehension | Multi-Perspective Context Matching | SQuAD 1.1 | | [paper](https://arxiv.org/pdf/1612.04211.pdf), [code] | 70 | | 2016 | Key-Value Memory Networks for Directly Reading Documents | Key-Value Memory Networks | WikiMovies, WikiQA | | [paper](https://aclweb.org/anthology/D16-1147/), [code](https://github.com/facebook/MemNN/tree/master/KVmemnn) | 71 | | 2016 | Iterative Alternating Neural Attention for Machine Reading | Iterative Attention Reader | Children’s Book Test, CNN and Daily Mail | | [paper](https://arxiv.org/pdf/1606.02245.pdf), [code]| 72 | | 2016 | A Thorough Examination of the CNN/Daily Mail Reading Comprehension Task | | CNN and Daily Mail | | [paper](https://www.aclweb.org/anthology/P16-1223.pdf), [code] | 73 | | 2015 | Teaching Machines to Read and Comprehend | Attentive Reader | CNN and Daily Mail | | [paper](https://papers.nips.cc/paper/5945-teaching-machines-to-read-and-comprehend.pdf), [code](https://github.com/thomasmesnard/DeepMind-Teaching-Machines-to-Read-and-Comprehend) | 74 | 75 | 76 | ## KBMRC: Knowledge-based Machine Reading Comprehension 77 | * Details: https://github.com/xanhho/Reading-Comprehension-Question-Answering-Papers/wiki/Knowledge-based-MRC 78 | 79 | ## OPQA: Open-domain Question Answering 80 | * Details: https://github.com/xanhho/Reading-Comprehension-Question-Answering-Papers/wiki/Open-domain-Question-Answering 81 | 82 | ## UQ: Unanswerable Questions 83 | * Details: https://github.com/xanhho/Reading-Comprehension-Question-Answering-Papers/wiki/Unanswerable-Questions 84 | 85 | ## Multi-Passage MRC: Multi-Passage Machine Reading Comprehension 86 | * Details: https://github.com/xanhho/Reading-Comprehension-Question-Answering-Papers/wiki/Multi-Passage-MRC 87 | 88 | ## CQA: Conversational Question Answering 89 | * Details: https://github.com/xanhho/Reading-Comprehension-Question-Answering-Papers/wiki/CQA 90 | 91 | 92 | ## Datasets 93 | - Following Danqi Chen, we have four answer types: 94 | * Cloze test 95 | * Multiple choice 96 | * Span extraction 97 | * Free answering 98 | 99 | - Details: https://github.com/xanhho/Reading-Comprehension-Question-Answering-Papers/wiki/MRC-Datasets 100 | 101 | | Year | Dataset | Task | Size | Source | Web/Paper | Answer type | Misc | Similar datasets | 102 | | ------------- | ------------- | ------------- | ------------- | ------------- | ------------- | ------------- | ------------- | ------------- | 103 | | 2019 | ROPES | RC | 14k | Wikipedia + science textbooks | [web](https://allennlp.org/ropes), [paper](https://arxiv.org/pdf/1908.05852.pdf) | Span extraction | background passage + situation | ShARC | 104 | |2019| RC-QED | RC | 12k | Wikipedia |[web](https://naoya-i.github.io/rc-qed/), [paper](https://arxiv.org/pdf/1910.04601.pdf)| Multiple choice | multi-passage | HotpotQA | 105 | |2019| QUOREF| RC | 24k+ | Wikipedia |[web](https://allennlp.org/quoref), [paper](https://www.aclweb.org/anthology/D19-1606.pdf)| Span extraction | coreference resolution | | 106 | |2019| COSMOS QA| | 35,600 | narrative |[web](https://wilburone.github.io/cosmos/), [paper](https://www.aclweb.org/anthology/D19-1243.pdf)| Multiple choice | | | 107 | |2019| DROP | RC | 96k | Wikipedia | [web](https://allennlp.org/drop), [paper](https://arxiv.org/pdf/1903.00161.pdf) | Span extraction + numerical reasoning | multi-span answers | | 108 | |2019| Natural Questions | RC | 323k | Wikipedia | [paper](https://www.aclweb.org/anthology/Q19-1026.pdf) | Span extraction | | | 109 | |2018|SQuAD 2.0| RC | 150k | Wikipedia |[paper](https://rajpurkar.github.io/SQuAD-explorer/)| Span extraction | no answer: 50k | NewsQA | 110 | |2018|MultiRC| RC | 6k+ questions | various articles | [web](https://cogcomp.seas.upenn.edu/multirc/), [paper](https://www.aclweb.org/anthology/N18-1023)| Multiple choice | multiple sentence reasoning | MCTest | 111 | |2018|CSQA| QA |200k dialogs, 1.6M turns ||[paper](https://arxiv.org/pdf/1801.10314.pdf)| | | | 112 | |2018| QuAC | RC | 100k | Wikipedia |[web](http://quac.ai/), [paper](https://arxiv.org/pdf/1808.07036.pdf) | Span extraction | conversational questions | CoQA | 113 | |2018| QAngaroo (Wikihop + Medhop) | RC | | Wikipedia + Medline |[web](https://qangaroo.cs.ucl.ac.uk/), [paper](https://transacl.org/ojs/index.php/tacl/article/viewFile/1325/299)| Multiple choice | multi-passage | HotpotQA | 114 | |2018| HotpotQA | RC | 113k | Wikipedia |[web](https://hotpotqa.github.io/), [paper](https://arxiv.org/pdf/1809.09600.pdf)| Span extraction | multi-passage | QAngaroo | 115 | |2018| CoQA | RC | 127k | various articles |[paper](https://stanfordnlp.github.io/coqa/)| Free answering | conversational questions | QuAC | 116 | |2018| ComplexWebQuestions | RC | 34,689 | WebQuestionsSP |[web](https://www.tau-nlp.org/compwebq), [paper](https://www.aclweb.org/anthology/N18-1059.pdf)| Span extraction? | multi-passage | | 117 | | 2018 | SWAG | QA | 113k | video caption | | Multiple choice | situational commonsense reasoning | | 118 | | 2018 | RecipeQA | RC | 36k | various | | | multimodal comprehension | | 119 | | 2018 | ProPara | RC | 2k | procedural text | | | | bAbI, SCoNE | 120 | | 2018 | OpenBookQA | QA | 6k | science facts | | Multiple choice | external knowledge | ARC | 121 | | 2018 | FEVER | | | | | | | | 122 | | 2018 | DuReader | | | | | Free answering | | | 123 | | 2018 | DuoRC | RC | 186k | movie plot | | Span extraction | | NarrativeQA | 124 | | 2018 | CLOTH | RC | 99k | English exams | | Cloze test | | RACE | 125 | | 2018 | CliCR | RC | 100k | clinical case text | | Cloze test | | | 126 | | 2018 | ARC | RC | 8k | science exam | | | easy 5197, challenge 2590 | | 127 | |2017|WikiSuggest||||[paper](https://aclweb.org/anthology/D15-1237)| | | | 128 | |2017|TriviaQA| RC | 96k question-answer pairs | Web + Wikipedia | [web](http://nlp.cs.washington.edu/triviaqa/), [paper](https://arxiv.org/pdf/1705.03551.pdf) | Span extraction | | SQuAD | 129 | |2017|SQA||||[paper](https://people.cs.umass.edu/~miyyer/pubs/2017_acl_dynsp.pdf)| | | | 130 | |2017|SearchQA||||[paper](https://arxiv.org/pdf/1704.05179.pdf)| Free answering | | | 131 | |2017|RACE||||[paper](http://www.cs.cmu.edu/~glai1/data/race/)| Multiple choice | | | 132 | |2017|NarrativeQA||||[paper](https://github.com/deepmind/narrativeqa)| Free answering | | | 133 | |2016|Who-did-What||||[paper](https://tticnlp.github.io/who_did_what/)| Cloze test | | | 134 | |2016|SQuAD 1.1| RC | 87k training + 10k development | Wikipedia |[paper](https://rajpurkar.github.io/SQuAD-explorer/)| Span extraction | | NewsQA | 135 | |2016|NewsQA||||[paper](https://datasets.maluuba.com/NewsQA)| Span extraction | | | 136 | |2016|MS MARCO||||[web](http://www.msmarco.org/dataset.aspx)| Free answering | | | 137 | |2016|LAMBADA||||[paper](http://clic.cimec.unitn.it/lambada/)| Cloze test | | | 138 | | 2016 | WikiMovies | QA | | | | | | | 139 | | 2015 | CuratedTREC | QA | | | | | | | 140 | |2015|CNN and Daily Mail| RC | 93k + 220k articles| CNN + Daily Mail |[paper](https://papers.nips.cc/paper/5945-teaching-machines-to-read-and-comprehend.pdf) [web](https://cs.nyu.edu/~kcho/DMQA/)| Cloze test | | | 141 | |2015|Children's Book Test| RC | 108 children's books | |[web](https://research.fb.com/downloads/babi/)| Cloze test | | | 142 | |2015|bAbI| RC | | classic text adventure game |[web](https://research.fb.com/downloads/babi/)| Free answering | 20 tasks | | 143 | | 2013 | WebQuestions | QA | | | | | | | 144 | |2013|QA4MRE| RC | | various articles |[paper](https://www.cs.cmu.edu/~hovy/papers/13CLEF-QA4MRE.pdf)| Multiple choice | | | 145 | |2013|MCTest| RC | 500 stories + 2k questions | fictional stories |[paper](http://aclweb.org/anthology/D13-1020)| Multiple choice | open-domain | | 146 | |1999|DeepRead| RC | 60 development and 60 test? | news stories|[paper](https://dl.acm.org/citation.cfm?id=1034678.1034731)| Free answering | | | 147 | 148 | 149 | ## Datasets with Explanations 150 | * Details: https://github.com/xanhho/Reading-Comprehension-Question-Answering-Papers/wiki/Datasets-with-Explanations 151 | 152 | ## QA over KG 153 | * Details: https://github.com/xanhho/Reading-Comprehension-Question-Answering-Papers/wiki/QA-over-KG 154 | 155 | ## Knowledge Bases/Knowledge Sources 156 | - Wikidata, [web](https://www.wikidata.org/wiki/Wikidata:Main_Page) 157 | - Freebase, [paper](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.538.7139&rep=rep1&type=pdf) 158 | - DBPedia 159 | 160 | 161 | ## Question Answering Systems 162 | - IBM's DeepQA 163 | - QuASE 164 | - Microsoft's AskMSR 165 | - YodaQA 166 | - DrQA 167 | 168 | 169 | ## Others (Misc: Model, transfer learning, data augmentation, domain adaption, cross lingual ...) 170 | - Minghao Hu, Yuxing Peng, Zhen Huang and Dongsheng Li, **A Multi-Type Multi-Span Network for Reading Comprehension that Requires Discrete Reasoning**, EMNLP 2019, [paper](https://www.aclweb.org/anthology/D19-1170.pdf). 171 | - Huazheng Wang, Zhe Gan, Xiaodong Liu, Jingjing Liu, Jianfeng Gao and Hongning Wang, **Adversarial Domain Adaptation for Machine Reading Comprehension**, EMNLP 2019, [paper](https://www.aclweb.org/anthology/D19-1254.pdf). 172 | - Yimin Jing, Deyi Xiong and Zhen Yan, **BiPaR: A Bilingual Parallel Dataset for Multilingual and Cross-lingual Reading Comprehension on Novels**, EMNLP 2019, [paper](https://www.aclweb.org/anthology/D19-1249.pdf). 173 | - Yiming Cui, Wanxiang Che, Ting Liu, Bing Qin, Shijin Wang and Guoping Hu, **Cross-Lingual Machine Reading Comprehension**, EMNLP 2019, [paper](https://www.aclweb.org/anthology/D19-1169.pdf). 174 | - Todor Mihaylov and Anette Frank, **Discourse-Aware Semantic Self-Attention for Narrative Reading Comprehension**, EMNLP 2019, [paper](https://www.aclweb.org/anthology/D19-1257.pdf). 175 | - Kyungjae Lee, Sunghyun Park, Hojae Han, Jinyoung Yeo, Seung-won Hwang and Juho Lee, **Learning with Limited Data for Multilingual Reading Comprehension**, EMNLP 2019, [paper](https://www.aclweb.org/anthology/D19-1283.pdf). 176 | - Qiu Ran, Yankai Lin, Peng Li, Jie Zhou and Zhiyuan Liu, **NumNet: Machine Reading Comprehension with Numerical Reasoning**, EMNLP 2019, [paper](https://www.aclweb.org/anthology/D19-1251.pdf). 177 | - Yiming Cui, Ting Liu, Wanxiang Che, Li Xiao, Zhipeng Chen, Wentao Ma, Shijin Wang and Guoping Hu, **A Span-Extraction Dataset for Chinese Machine Reading Comprehension**, EMNLP 2019, [paper](https://www.aclweb.org/anthology/D19-1600.pdf). 178 | - Daniel Andor, Luheng He, Kenton Lee and Emily Pitler, **Giving BERT a Calculator: Finding Operations and Arguments with Reading Comprehension**, EMNLP 2019, [paper](https://www.aclweb.org/anthology/D19-1609.pdf). 179 | - Tsung-Yuan Hsu, Chi-Liang Liu and Hung-yi Lee, **Zero-shot Reading Comprehension by Cross-lingual Transfer Learning with Multi-lingual Language Representation Model**, EMNLP 2019, [paper](https://www.aclweb.org/anthology/D19-1607.pdf). 180 | - Kyosuke Nishida et al., **Multi-style Generative Reading Comprehension**, ACL 2019, [paper](https://www.aclweb.org/anthology/P19-1220). 181 | - Alon Talmor and Jonathan Berant, **MultiQA: An Empirical Investigation of Generalization and Transfer in Reading Comprehension**, ACL 2019, [paper](https://www.aclweb.org/anthology/P19-1485). 182 | - Yi Tay et al., **Simple and Effective Curriculum Pointer-Generator Networks for Reading Comprehension over Long Narratives**, ACL 2019, [paper](https://www.aclweb.org/anthology/P19-1486). 183 | - Haichao Zhu et al., **Learning to Ask Unanswerable Questions for Machine Reading Comprehension**, ACL 2019, [paper](https://www.aclweb.org/anthology/P19-1415). 184 | - Patrick Lewis et al., **Unsupervised Question Answering by Cloze Translation**, ACL 2019, [paper](https://www.aclweb.org/anthology/P19-1484.pdf). 185 | - Michael Hahn and Frank Keller, **Modeling Human Reading with Neural Attention**, EMNLP 2016, [paper](https://www.aclweb.org/anthology/D16-1009.pdf). 186 | - Jianpeng Cheng et al., **Long Short-Term Memory-Networks for Machine Reading**, EMNLP 2016, [paper](https://www.aclweb.org/anthology/D16-1053.pdf). 187 | 188 | 189 | ## Thanks to these repositories: 190 | - https://github.com/penzant/nlu_datasets_2018 191 | - https://github.com/seriousmac/awesome-qa 192 | 193 | 194 | 195 | 196 | --------------------------------------------------------------------------------