├── README.md ├── boosting_nlp_skills.md ├── dialogue-system.md └── nlp_meeting_list.md /README.md: -------------------------------------------------------------------------------- 1 | # nlp-paper-reading-list 2 | 系统整理NLP各个方向需要阅读的论文 3 | 4 | - [对话系统](./dialogue-system.md) 5 | - [自动摘要](http://pfliu.com/Historiography/summarization/summ.html) 6 | - [问答](https://github.com/seriousran/awesome-qa) 7 | 8 | 9 | 10 | NLPer可投的论文列表 11 | 12 | - [会议列表](./nlp_meeting_list.md) 13 | 14 | 了解NLP主流技术的文章、博客等 15 | - [boosting_nlp_skills.md](./boosting_nlp_skills.md) 16 | -------------------------------------------------------------------------------- /boosting_nlp_skills.md: -------------------------------------------------------------------------------- 1 | ## Boosting NLP Skills 2 | 3 | NLP核心技能的入门文章、资源等（适合用于初学者自学）。大家可以把自己看到的好文章记录到这里，不断扩充列表，给之后来实验室的同学一个指引。 4 | 5 | ### 词向量 - Word Embeddings 6 | - [从Word Embedding到Bert模型—自然语言处理中的预训练技术发展史](https://zhuanlan.zhihu.com/p/49271699) 7 | 8 | ### 预训练语言模型 - BERT etc. 9 | - [乘风破浪的PTM：两年来预训练模型的技术进展](https://zhuanlan.zhihu.com/p/254821426) 10 | 11 | ### 注意力机制 - Attention Mechanism 12 | - [深度学习中的注意力模型（2017版）](https://zhuanlan.zhihu.com/p/37601161) 13 | - [Attention机制简单总结](https://zhuanlan.zhihu.com/p/46313756) 14 | 15 | ### Transformer 16 | - [The Illustrated Transformer](http://jalammar.github.io/illustrated-transformer/)：感觉是最好的Transformer讲解，配合图示很容易懂，知乎上有很多翻译，例如[这个](https://zhuanlan.zhihu.com/p/196642078)和[这个](https://zhuanlan.zhihu.com/p/48508221) 17 | - [放弃幻想，全面拥抱Transformer：自然语言处理三大特征抽取器（CNN/RNN/TF）比较](https://zhuanlan.zhihu.com/p/54743941)：Transformer和传统序列建模方法RNN、CNN的比较 18 | 19 | ### LSTM 20 | - [探索LSTM：基本概念到内部结构](https://zhuanlan.zhihu.com/p/27345523) 21 | - [理解 LSTM 网络](https://www.jianshu.com/p/9dc9f41f0b29) 22 | - [循环神经网络(RNN)模型与前向反向传播算法](https://www.cnblogs.com/pinard/p/6509630.html) 23 | - [LSTM模型与前向反向传播算法 - 刘建平Pinard - 博客园](http://www.cnblogs.com/pinard/p/6519110.html) 24 | 25 | ### 对话系统 26 | - [小哥哥，检索式chatbot了解一下？](https://mp.weixin.qq.com/s?__biz=MzIwNzc2NTk0NQ==&mid=2247484934&idx=1&sn=40332a00a0a8f4b3943ec0dae35d5c5a&chksm=970c2ed0a07ba7c67248524c08b1cb49217598c93a3b4ba2a8eda053a443136a3a8c578c4121&mpshare=1&scene=1&srcid=1025u0YxSzNgMKTRzA1m7VzL#rd) 27 | 28 | ### 序列标注（分词、命名实体识别、口语理解） 29 | - [自然语言处理之序列标注问题](http://www.cnblogs.com/jiangxinyang/p/9368482.html) 30 | 31 | ### 推荐博主 32 | - 【知乎】张俊林 33 | - 【微信公众号、知乎专栏】夕小瑶的卖萌屋 34 | -------------------------------------------------------------------------------- /dialogue-system.md: -------------------------------------------------------------------------------- 1 | # Dialogue System Papers Reading List 2 | 对话系统方向的论文整理 3 | 4 | # Bookmarks 5 | * [综述类](#综述类) 6 | * [Dataset](#dataset) 7 | * [Evaluation metrics](#evaluation-metrics) 8 | * [非任务型对话](#非任务型对话) 9 | * [任务型对话](#任务型对话) 10 | * [Reinforcement Learning](#reinforcement-learning) 11 | * [引入背景知识](#引入背景知识) 12 | * [Domain Adaptation](#domain-adaptation) 13 | * [待整理](#待整理) 14 | 15 | 16 | 17 | ## 综述类 18 | 19 | - 李纪为博士论文 [teaching machines to converse](https://github.com/topics/teaching-machines-to-converse) 20 | - 微软小冰产品设计结构 [The Design and Implementation of XiaoIce, an Empathetic Social Chatbot](https://arxiv.org/pdf/1812.08989v1.pdf) 21 | - 黄民烈组综述论文 [Challenges in Building Intelligent Open-domain Dialog Systems]((https://arxiv.org/abs/1905.05709)) 22 | 23 | ## Dataset 24 | * Budzianowski, Paweł, et al. **“MultiWOZ - A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modelling.”**Empirical Methods in Natural Language Processing, 2018, pp. 5016–5026. 25 | * [A Survey of Available Corpora For Building Data-Driven Dialogue Systems](http://arxiv.org/pdf/1512.05742v2.pdf), Iulian Vlad Serban et al., *arXiv*, 2015. 26 | * [OpenSubtitles2016: Extracting Large Parallel Corpora from Movie and TV Subtitles](http://stp.lingfil.uu.se/~joerg/paper/opensubs2016.pdf), Pierre Lison et al. (3.36 million subtitles) 27 | * [Building End-To-End Dialogue Systems 28 | Using Generative Hierarchical Neural Network Models](https://arxiv.org/pdf/1507.04808.pdf), Iulian V. Serban et al., *AAAI*, 2015. (500 movies) 29 | * [Conversational Contextual Cues: The Case of Personalization and History for Response Ranking](https://arxiv.org/pdf/1606.00372v1.pdf), Rami Al-Rfou et al., *arXiv*, 2016. (Reddit comments) 30 | * [The Ubuntu Dialogue Corpus: A Large Dataset for Research in Unstructured Multi-Turn Dialogue Systems](http://arxiv.org/pdf/1506.08909v3.pdf), Ryan Lowe et al., SIGDial 2015. [[dataset](https://github.com/rkadlec/ubuntu-ranking-dataset-creator)] 31 | * **Frames:** A Corpus for Adding Memory to Goal-Oriented Dialogue Systems, Layla El Asri et al., Microsoft Maluuba. SIGDial 2017. [[paper](http://www.aclweb.org/anthology/W17-5526)] [[dataset](http://datasets.maluuba.com/Frames)] 32 | 33 | 34 | 35 | ## Evaluation metrics 36 | 37 | - [How NOT To Evaluate Your Dialogue System: An Empirical Study of Unsupervised Evaluation Metrics for Dialogue Response Generation](https://arxiv.org/pdf/1603.08023v1.pdf), Chia-Wei Liu et al., *arXiv*, 2016. 38 | - [Relevance of Unsupervised Metrics in Task-Oriented Dialogue for 39 | Evaluating Natural Language Generation](https://arxiv.org/pdf/1706.09799.pdf), Shikhar Sharma et al., Microsoft Maluuba. *arXiv* 2017. [[code](https://github.com/Maluuba/nlg-eval)] 40 | 41 | 42 | 43 | ## 非任务型对话 44 | 45 | - **AliMe**: "AliMe Chat: A Sequence to Sequence and Rerank based Chatbot Engine". ACL(2017) [[PDF]](./papers/dialogue-system/P17-2079.pdf) :star: 46 | - **ECM**: "Emotional Chatting Machine: Emotional Conversation Generation with Internal and External Memory". AAAI(2018) [[PDF]](./papers/dialogue-system/16455-76513-1-PB.pdf) [[code]](https://github.com/tuxchow/ecm) :star::star::star::star: 47 | - **DUA**: "Modeling Multi-turn Conversation with Deep Utterance Aggregation". COLING(2018) [[PDF]](./papers/dialogue-system/C18-1317.pdf) [[code]](https://github.com/cooelf/DeepUtteranceAggregation) :star::star: 48 | - **Edit-N-Rerank**: "Response Generation by Context-aware Prototype Editing". AAAI(2019) [[PDF]](./papers/dialogue-system/1806.07042.pdf) [[code]](https://github.com/MarkWuNLP/ResponseEdit) :star::star::star: 49 | - **PCCM**: "Assigning Personality/Profile to a Chatting Machine for Coherent Conversation Generation". IJCAI(2018) [[PDF]](./papers/dialogue-system/IJCAI-0595.pdf) [[code]](https://github.com/qianqiao/AssignPersonality) :star::star::star::star: 50 | - **Retrieval+multi-seq2seq**: "An Ensemble of Retrieval-Based and Generation-Based Human-Computer Conversation Systems". IJCAI(2018) [[PDF]](./papers/dialogue-system/IJCAI-0609.pdf) :star::star::star: 51 | 52 | 引入personality保持对话一致 53 | 54 | - Li J, Galley M, Brockett C, et al.**A Persona-Based Neural Conversation Model**[J]. meeting of the association for computational linguistics, 2016: 994-1003. 55 | - Qian Q, Huang M, Zhao H, et al. **Assigning Personality/Profile to a Chatting Machine for Coherent Conversation Generation**[J]. international joint conference on artificial intelligence, 2018: 4279-4285. 56 | - Eric Chu, Prashanth Vijayaraghavan, Deb Roy. **"Learning Personas from Dialogue with Attentive Memory Networks."** EMNLP (2018). 57 | - Saizheng Zhang,Emily Dinan,Jack Urbanek,Arthur Szlam,Douwe Kiela,Jason Weston **Personalizing Dialogue Agents: I have a dog, do you have pets too?**AAAI2018 58 | - Kaixiang Mo, Shuangyin Li, Yu Zhang, Jiajun Li, Qiang Yang**Personalizing a Dialogue System with Transfer Learning.**AAAI2018 59 | 60 | ## 任务型对话 61 | 62 | - **Multi-level Mem**: "Multi-Level Memory for Task Oriented Dialogs". NAACL(2019) [[PDF]](./papers/dialogue-system/N19-1375.pdf) :star::star::star: 63 | - **BossNet**: "Disentangling Language and Knowledge in Task-Oriented Dialogs 64 | ". NAACL(2019) [[PDF]](./papers/dialogue-system/N19-1126.pdf) [[code]](https://github.com/dair-iitd/BossNet) :star::star::star: 65 | - **Mem2Seq**: "Mem2Seq: Effectively Incorporating Knowledge Bases into End-to-End Task-Oriented Dialog Systems". ACL(2018) [[PDF]](./papers/dialogue-system/P18-1136.pdf) [[code]](https://github.com/HLTCHKUST/Mem2Seq) :star::star::star::star: 66 | - **SMN**: "Sequential Matching Network: A New Architecture for Multi-turn Response Selection in Retrieval-Based Chatbots". ACL(2017) [[PDF]](./papers/dialogue-system/P17-1046.pdf) [[code]](https://github.com/MarkWuNLP/MultiTurnResponseSelection) :star::star::star::star: 67 | - **KVR Net**: "Key-Value Retrieval Networks for Task-Oriented Dialogue". SIGDIAL(2017) [[PDF]](./papers/dialogue-system/W17-5506.pdf) [[data]](https://nlp.stanford.edu/blog/a-new-multi-turn-multi-domain-task-oriented-dialogue-dataset/) :star::star: 68 | - **Pretrain-Fine-tune**: "Training Neural Response Selection for Task-Oriented Dialogue Systems". ACL(2019) [[PDF]](./papers/dialogue-system/1906.01543.pdf) [[data]](https://github.com/PolyAI-LDN/conversational-datasets) :star::star::star: 69 | - [A Network-based End-to-End Trainable Task-oriented Dialogue System](http://arxiv.org/pdf/1604.04562v2.pdf), Tsung-Hsien Wen et al., *arXiv*, 2016. 70 | - **DSR**: "Sequence-to-Sequence Learning for Task-oriented Dialogue with Dialogue State Representation". COLING(2018) [[PDF]](./papers/dialogue-system/C18-1320.pdf) :star::star: 71 | 72 | ### DST 73 | 74 | - **Trade:** Transferable Multi-Domain State Generator for Task-Oriented Dialogue Systems.ACL(2019) [[paper](https://arxiv.org/pdf/1905.08743.pdf)] [[code]](https://github.com/jasonwu0731/trade-dst) :star::star::star::star: 75 | 76 | 77 | 78 | ## Reinforcement Learning 79 | 80 | * [Deep Reinforcement Learning for Dialogue Generation](https://arxiv.org/pdf/1606.01541.pdf), Jiwei Li et al., *arXiv*, 2016. 81 | 82 | * [End-to-end LSTM-based dialog control optimized with supervised and reinforcement learning](https://arxiv.org/pdf/1606.01269v1.pdf), Jason D. Williams and Geoffrey Zweig., *arXiv*, 2016. 83 | 84 | * [A Network-based End-to-End Trainable Task-oriented Dialogue System](http://arxiv.org/pdf/1604.04562v2.pdf), Tsung-Hsien Wen et al., *arXiv*, 2016. 85 | 86 | * [SimpleDS: A Simple Deep Reinforcement Learning Dialogue System](http://arxiv.org/pdf/1601.04574v1.pdf), Heriberto Cuayahuitl, *arXiv*, 2016. 87 | 88 | * [Towards Interpretable Chit-chat: Open Domain Dialogue Generation with Dialogue Acts](https://openreview.net/pdf?id=Bym0cU1CZ), 2017. 89 | 90 | * [End-to-End Task-Completion Neural Dialogue Systems](https://arxiv.org/pdf/1703.01008.pdf), Xiujun Li et al., *arXiv*, 2018. 91 | 92 | * Jiwei Li, Will Monroe, Alan Ritter, Michel Galley, Jianfeng Gao, and Dan Jurafsky. 2016d. **Deep reinforcement learning for dialogue generation.** EMNLP . 93 | 94 | * Jiwei Li, Will Monroe, and Dan Jurafsky. 2017c. **Learning to decode for future success**. arXiv preprint arXiv:1701.06549 . 95 | 96 | * Zhou G, Luo P, Xiao Y, et al. **Elastic Responding Machine for Dialog Generation with Dynamically Mechanism Selecting**[C]. national conference on artificial intelligence, 2018: 5730-5737. 97 | 98 | * Liu, Bing, et al. **“Customized Nonlinear Bandits for Online Response Selection in Neural Conversation Models.”** National Conference on Artificial Intelligence, 2018, pp. 5245–5252 99 | 100 | * **RL-Dialogue**: "Deep Reinforcement Learning for Dialogue Generation". EMNLP(2016) [[PDF]](./papers/dialogue-system/D16-1127.pdf) :star: 101 | 102 | 103 | 104 | ## 引入背景知识 105 | 106 | * [Evaluating Prerequisite Qualities For Learning End-to-End Dialog Systems](http://arxiv.org/pdf/1511.06931v6.pdf), Jesse Dodge et al., Facebook AI Research, ICLR 2016. 107 | * [Dialog-based Language Learning](https://arxiv.org/pdf/1604.06045v4.pdf), Jason Weston, *arXiv*, 2016. 108 | * [Learning End-to-End Goal-Oriented Dialog](https://arxiv.org/pdf/1605.07683.pdf), Antoine Bordes and Jason Weston, *arXiv*, 2016. 109 | * Zhou H, Young T, Huang M, et al. **Commonsense Knowledge Aware Conversation Generation with Graph Attention**[C]. international joint conference on artificial intelligence, 2018: 4623-4629. 110 | * He H, Balakrishnan A, Eric M, et al. **Learning Symmetric Collaborative Dialogue Agents with Dynamic Knowledge Graph Embeddings**[J]. meeting of the association for computational linguistics, 2017: 1766-1776. 111 | * Li J, Miller A H, Chopra S, et al. **Learning through Dialogue Interactions by Asking Questions**[J]. international conference on learning representations, 2017. 112 | * Ghazvininejad M, Brockett C, Chang M, et al. **A Knowledge-Grounded Neural Conversation Model**[J]. national conference on artificial intelligence, 2018: 5110-5117. 113 | * Zhu W, Mo K, Zhang Y, et al. **Flexible End-to-End Dialogue System for Knowledge Grounded Conversation.**[J]. arXiv: Computation and Language, 2017. 114 | * Guo, Daya, et al. **“Dialog-to-Action: Conversational Question Answering Over a Large-Scale Knowledge Base.”** NIPS 2018: The 32nd Annual Conference on Neural Information Processing Systems, 2018, pp. 2946–2955 115 | * Fan Wang Jinhua Peng Hua Wu Rongzhong Lian, Min Xie. **Learning to select knowledge for response generation in dialog systems.** arXiv preprint arXiv:1902.04911, 2019. 116 | * **Mem2Seq: Effectively Incorporating Knowledge Bases into End-to-End Task-Oriented Dialog Systems** ACL2018 117 | * **PostKS**: "Learning to Select Knowledge for Response Generation in Dialog Systems". arXiv(2019) [[PDF]](./papers/dialogue-system/1902.04911.pdf) :star::star: 118 | * **CAS**: "Skeleton-to-Response: Dialogue Generation Guided by Retrieval Memory". NAACL(2019) [[PDF]](./papers/dialogue-system/N19-1124.pdf) [[code]](https://github.com/jcyk/Skeleton-to-Response) :star::star::star: 119 | 120 | 121 | 122 | 123 | ## Domain Adaptation 124 | * [Multi-domain Neural Network Language Generation for Spoken Dialogue Systems](http://mi.eng.cam.ac.uk/~sjy/papers/wgmr16.pdf), Tsung-Hsien Wen et al. 125 | 126 | * [Domain Adaptation with Unlabeled Data for Dialog Act Tagging](http://ttic.uchicago.edu/~klivescu/papers/margolis_etal_danlp2010.pdf), Anna Margolis et al. 127 | 128 | * [Learning Domain-Independent Dialogue Policies via Ontology Parameterisation](http://mi.eng.cam.ac.uk/~sjy/papers/wsws15.pdf), Zhuoran Wang et al. 129 | 130 | 131 | 132 | ## Variational Autoencoders 133 | 134 | * [A Conditional Variational Framework for Dialog Generation](https://arxiv.org/pdf/1705.00316.pdf), Xiaoyu Shen, *arXiv*, 2017. 135 | 136 | 137 | 138 | ## 待整理 139 | 140 | - [OpenSubtitles2016: Extracting Large Parallel Corpora from Movie and TV Subtitles](http://stp.lingfil.uu.se/~joerg/paper/opensubs2016.pdf), Pierre Lison et al., 2016 (3.36 million subtitles) 141 | - [Building End-To-End Dialogue Systems 142 | Using Generative Hierarchical Neural Network Models](https://arxiv.org/pdf/1507.04808.pdf), Iulian V. Serban et al., *AAAI*, 2015. (500 movies) 143 | - [A Hierarchical Latent Variable Encoder-Decoder 144 | Model for Generating Dialogues](https://arxiv.org/pdf/1605.06069v3.pdf), Iulian V. Serban et al., *arXiv*, 2016. 145 | - [Multiresolution Recurrent Neural Networks: An Application to Dialogue Response Generation](https://arxiv.org/pdf/1606.00776v2.pdf), Iulian Vlad Serban et al., *arXiv*, 2016. 146 | - [LSTM based Conversation Models](http://arxiv.org/pdf/1603.09457v1.pdf), Yi Luan et al., *arXiv*, 2016. 147 | - [End-to-end LSTM-based dialog control optimized with supervised and reinforcement learning](https://arxiv.org/pdf/1606.01269v1.pdf), Jason D. Williams and Geoffrey Zweig., Microsoft Research, *arXiv*, 2016. 148 | - [Conversational Contextual Cues: The Case of Personalization and History for Response Ranking](https://arxiv.org/pdf/1606.00372v1.pdf), Rami Al-Rfou et al., Google Inc, *arXiv*, 2016. 149 | - [Learning End-to-End Goal-Oriented Dialog](https://arxiv.org/pdf/1605.07683.pdf), Antoine Bordes and Jason Weston, Facebook AI Research, *arXiv*, 2016. 150 | - [Evaluating Prerequisite Qualities For Learning End-to-End Dialog Systems](http://arxiv.org/pdf/1511.06931v6.pdf), Jesse Dodge et al., Facebook AI Research, ICLR 2016. 151 | - [The Ubuntu Dialogue Corpus: A Large Dataset for Research in Unstructured Multi-Turn Dialogue Systems](http://arxiv.org/pdf/1506.08909v3.pdf), Ryan Lowe et al., *SIGDial*, 2015. [[dataset](https://github.com/rkadlec/ubuntu-ranking-dataset-creator)] 152 | - [How NOT To Evaluate Your Dialogue System: An Empirical Study of Unsupervised Evaluation Metrics for Dialogue Response Generation](https://arxiv.org/pdf/1603.08023v1.pdf), Chia-Wei Liu et al., *arXiv*, 2016. 153 | - [A Survey of Available Corpora For Building Data-Driven Dialogue Systems](http://arxiv.org/pdf/1512.05742v2.pdf), Iulian Vlad Serban et al., *arXiv*, 2015. 154 | - [Neural Responding Machine for Short-Text Conversation](https://arxiv.org/pdf/1503.02364v2.pdf), Lifeng Shang et al., *arXiv*, 2015. 155 | - [A Neural Conversational Model](https://arxiv.org/pdf/1506.05869.pdf), Oriol Vinyals et al., *arXiv*, 2015. 156 | - [A Neural Network Approach to Context-Sensitive Generation of Conversational Responses](http://arxiv.org/pdf/1506.06714v1.pdf), Alessandro Sordoni et al., *NAACL*, 2015. 157 | - [A Diversity-Promoting Objective Function for Neural Conversation Models](http://arxiv.org/pdf/1510.03055v3.pdf), Jiwei Li et al., *NAACL*, 2016. (Maximum Mutual Information) 158 | - [A Persona-Based Neural Conversation Model](http://arxiv.org/pdf/1603.06155v2.pdf), Jiwei Li et al., *ACL*, 2016. 159 | - [Neural Net Models for Open-Domain Discourse Coherence](https://arxiv.org/pdf/1606.01545.pdf), Jiwei Li et al., *arXiv*, 2016. 160 | - [SimpleDS: A Simple Deep Reinforcement Learning Dialogue System](http://arxiv.org/pdf/1601.04574v1.pdf), Heriberto Cuayahuitl, *arXiv*, 2016. 161 | - [End-To-End Generative Dialogue](https://github.com/michaelfarrell76/End-To-End-Generative-Dialogue/blob/master/paper/main.pdf), Colton Gyulay et al. [[code](https://github.com/michaelfarrell76/End-To-End-Generative-Dialogue)] 162 | - [A Conditional Variational Framework for Dialog Generation](https://arxiv.org/pdf/1705.00316.pdf), Xiaoyu Shen, *arXiv*, 2017. 163 | - [Towards Interpretable Chit-chat: Open Domain Dialogue Generation with Dialogue Acts](https://openreview.net/pdf?id=Bym0cU1CZ), 2017. 164 | - [Relevance of Unsupervised Metrics in Task-Oriented Dialogue for 165 | Evaluating Natural Language Generation](https://arxiv.org/pdf/1706.09799.pdf), Shikhar Sharma et al., Microsoft Maluuba. *arXiv* 2017. [[code](https://github.com/Maluuba/nlg-eval)] 166 | 167 | - **PAML**: "Personalizing Dialogue Agents via Meta-Learning". ACL(2019) [[PDF]](./papers/dialogue-system/1905.10033.pdf) [[code]](https://github.com/HLTCHKUST/PAML) :star::star::star: 168 | - **GLMP**: "Global-to-local Memory Pointer Networks for Task-Oriented Dialogue". ICLR(2019) [[PDF]](./papers/dialogue-system/1901.04713.pdf) [[code]](https://github.com/jasonwu0731/GLMP) :star::star::star::star: 169 | - **Two-Stage-Transformer**: "Wizard of Wikipedia: Knowledge-Powered Conversational agents". ICLR(2019) [[PDF]](./papers/dialogue-system/1811.01241.pdf) :star::star: 170 | - **Survey of Dialogue Corpora**: "A Survey of Available Corpora For Building Data-Driven Dialogue Systems: The Journal Version". Dialogue & Discourse(2018) [[PDF]](./papers/dialogue-system/3690-7705-1-PB.pdf) :star: 171 | - **D2A**: "Dialog-to-Action: Conversational Question Answering Over a Large-Scale Knowledge Base". NIPS(2018) [[PDF]](./papers/dialogue-system/7558-dialog-to-action.pdf) :star::star: 172 | - **DAIM**: "Generating Informative and Diverse Conversational Responses via Adversarial Information Maximization". NIPS(2018) [[PDF]](./papers/dialogue-system/7452-generating-informative.pdf) :star::star: 173 | - **LU-DST**: "Multi-task Learning for Joint Language Understanding and Dialogue State Tracking". SIGDIAL(2018) [[PDF]](./papers/dialogue-system/W18-5045.pdf) :star::star::star: 174 | - **MTask**: "A Knowledge-Grounded Neural Conversation Model". AAAI(2018) [[PDF]](./papers/dialogue-system/16710-76819-1-PB.pdf) :star: 175 | - **MTask-M**: "Multi-Task Learning for Speaker-Role Adaptation in Neural Conversation Models". IJCNLP(2018) [[PDF]](./papers/dialogue-system/I17-1061.pdf) :star: 176 | - **GenDS**: "Flexible End-to-End Dialogue System for Knowledge Grounded Conversation". arXiv(2017) [[PDF]](./papers/dialogue-system/1709.04264.pdf) :star::star: 177 | - **SL+RL**: "Dialogue Learning with Human Teaching and Feedback in End-to-End Trainable Task-Oriented Dialogue Systems". NAACL(2018) [[PDF]](./papers/dialogue-system/N18-1187.pdf) :star::star::star: 178 | - **Time-Decay-SLU**: "How Time Matters: Learning Time-Decay Attention for Contextual Spoken Language Understanding in Dialogues". NAACL(2018) [[PDF]](./papers/dialogue-system/N18-1194.pdf) [[code]](https://github.com/MiuLab/Time-Decay-SLU) :star::star::star::star: 179 | - **REASON**: "Dialog Generation Using Multi-turn Reasoning Neural Networks". NAACL(2018) [[PDF]](./papers/dialogue-system/N18-1186.pdf) :star::star::star: 180 | - **ADVMT**: "One “Ruler” for All Languages: Multi-Lingual Dialogue Evaluation with Adversarial Multi-Task Learning". IJCAI(2018) [[PDF]](./papers/dialogue-system/IJCAI-0616.pdf) :star::star: 181 | - **STD/HTD**: "Learning to Ask Questions in Open-domain Conversational Systems with Typed Decoders". ACL(2018) [[PDF]](./papers/dialogue-system/P18-1204.pdf) [[code]](https://github.com/victorywys/Learning2Ask_TypedDecoder) :star::star::star: 182 | - **CSF used**: "Generating Informative Responses with Controlled Sentence Function". ACL(2018) [[PDF]](./papers/dialogue-system/P18-1139.pdf) [[code]](https://github.com/kepei1106/SentenceFunction) :star::star::star: 183 | - **NKD**: "Knowledge Diffusion for Neural Dialogue Generation". ACL(2018) [[PDF]](./papers/dialogue-system/P18-1138.pdf) [[data]](https://github.com/liushuman/neural-knowledge-diffusion) :star::star: 184 | - **DAWnet**: "Chat More: Deepening and Widening the Chatting Topic via A Deep Model". SIGIR(2018) [[PDF]](./papers/dialogue-system/p255-wang.pdf) [[code]](https://sigirdawnet.wixsite.com/dawnet) :star::star::star: 185 | - **ZSDG**: "Zero-Shot Dialog Generation with Cross-Domain Latent Actions". SIGDIAL(2018) [[PDF]](./papers/dialogue-system/W18-5001.pdf) [[code]](https://github.com/snakeztc/NeuralDialog-ZSDG) :star::star::star: 186 | - **Data-Aug**: "Sequence-to-Sequence Data Augmentation for Dialogue Language Understanding". COLING(2018) [[PDF]](./papers/dialogue-system/C18-1105.pdf) [[code]](https://github.com/AtmaHou/Seq2SeqDataAugmentationForLU) :star::star: 187 | - 188 | - **DC-MMI**: "Generating More Interesting Responses in Neural Conversation Models with Distributional Constraints". EMNLP(2018) [[PDF]](./papers/dialogue-system/D18-1431.pdf) [[code]](https://github.com/abaheti95/DC-NeuralConversation) :star::star: 189 | - **cVAE-XGate/CGate**: "Better Conversations by Modeling, Filtering, and Optimizing for Coherence and Diversity". EMNLP(2018) [[PDF]](./papers/dialogue-system/D18-1432.pdf) [[code]](https://github.com/XinnuoXu/CVAE_Dial) :star::star::star: 190 | - **MMI**: "A Diversity-Promoting Objective Function for Neural Conversation Models". NAACL-HLT(2016) [[PDF]](./papers/dialogue-system/N16-1014.pdf) [[code]](https://github.com/jiweil/Neural-Dialogue-Generation) :star::star: 191 | - **TA-Seq2Seq**: "Topic Aware Neural Response Generation". AAAI(2017) [[PDF]](./papers/dialogue-system/AAAI17_TA-Seq2Seq.pdf) [[code]](https://github.com/LynetteXing1991/TA-Seq2Seq) :star::star: 192 | - **MA**: "Mechanism-Aware Neural Machine for Dialogue Response Generation". AAAI(2017) [[PDF]](./papers/dialogue-system/14471-66751-1-PB.pdf) :star::star: 193 | - **HRED**: "Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models". AAAI(2016) [[PDF]](./papers/dialogue-system/11957-56353-1-PB.pdf) [[code]](https://github.com/julianser/hed-dlg) :star::star: 194 | - **VHRED**: "A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues". AAAI(2017) [[PDF]](./papers/dialogue-system/14567-66703-1-PB.pdf) [[code]](https://github.com/julianser/hed-dlg-truncated) :star::star: 195 | - **CVAE/KgCVAE**: "Learning Discourse-level Diversity for Neural Dialog Models using Conditional Variational Autoencoders". ACL(2017) [[PDF]](./papers/dialogue-system/P17-1061.pdf) [[code]](https://github.com/snakeztc/NeuralDialog-CVAE) :star::star::star: 196 | - **ERM**: "Elastic Responding Machine for Dialog Generation with Dynamically Mechanism Selecting". AAAI(2018) [[PDF]](./papers/dialogue-system/16316-76896-1-PB.pdf) :star::star: 197 | - **Tri-LSTM**: "Augmenting End-to-End Dialogue Systems With Commonsense Knowledge". AAAI(2018) [[PDF]](./papers/dialogue-system/16573-76790-1-PB.pdf) :star::star: 198 | - **Dual Fusion**: "Smarter Response with Proactive Suggestion: A New Generative Neural Conversation Paradigm". IJCAI(2018) [[PDF]](./papers/dialogue-system/IJCAI-0629.pdf) :star::star::star: 199 | - **CCM**: "Commonsense Knowledge Aware Conversation Generation with Graph Attention". IJCAI(2018) [[PDF]](./papers/dialogue-system/IJCAI-0643.pdf) [[code]](https://github.com/tuxchow/ccm) :star::star::star::star::star: 200 | - **Topic-Seg-Label**: "A Weakly Supervised Method for Topic Segmentation and Labeling in Goal-oriented Dialogues via Reinforcement Learning". IJCAI(2018) [[PDF]](./papers/dialogue-system/IJCAI-0612.pdf) [[code]](https://github.com/truthless11/Topic-Seg-Label) :star::star::star::star: 201 | - 基于GAN的对话系统 202 | - Xu Z, Liu B, Wang B, et al. **Neural Response Generation via GAN with an Approximate Embedding Layer.**[C]. empirical methods in natural language processing, 2017: 617-626. 203 | - Young, Tom, et al. **Augmenting End-to-End Dialogue Systems with Commonsense Knowledge.”**National Conference on Artificial Intelligence, 2018, pp. 4970–4977. 204 | - Zhang, Yizhe, et al. **“Generating Informative and Diverse Conversational Responses via Adversarial Information Maximization.”** Neural Information Processing Systems, 2018, pp. 1815–1825. 205 | - 对话历史信息建模 206 | - Xing C, Wu Y, Wu W, et al. **Hierarchical Recurrent Attention Network for Response Generation**[J]. national conference on artificial intelligence, 2018: 5610-5617. 207 | - Ruizhe Li, Chenghua Lin, Matthew Collinson, Xiao Li, Guanyi Chen. "**A Dual-Attention Hierarchical Recurrent Neural Network for Dialogue Act Classification**." arXiv:1810.09154 (2018). 208 | 209 | 210 | 211 | ## Reference 212 | 213 | 214 | 215 | 216 | 217 | -------------------------------------------------------------------------------- /nlp_meeting_list.md: -------------------------------------------------------------------------------- 1 | # NLP会议列表 2 | 3 | 4 | | CCF分类 | 会议名称 | 举办地点 | Abstraction Registration Due | submission Deadline | Notification Due | Final Version Due | 官 网 | 5 | | ------- | ------------------------- | -------------------------------------- | ---------------------------- | ------------------- | ------------------ | ------------------- | ------------------------------------------------------ | 6 | | | IREC 2020 | Hammamet. Tunisia | Sept 6, 2020 | Sept 16, 2020 | Sept 30, 2020 | Oct 10, 2020 | https://irec-conference.com/ | 7 | | | CCL 2020 | 海南 | | June 1, 2020 | July 15, 2020 | August 1, 2020 | http://www.cips-cl.org/static/CCL2020/index.html | 8 | | | COLING 2020 | Barcelona, Spain | | Jul 1, 2020 | Oct 1, 2020 | Nov 1, 2020 | [https://coling2020.org](https://coling2020.org/) | 9 | | | CoNLL 2020 | Punta Cana, Dominican Republic | | June 5, 2020 | August 28, 2020 | | https://www.conll.org/ | 10 | | | STARSEM 2020 | Barcelona, Spain | | July 20, 2020 | Sept 21, 2020 | | https://sites.google.com/view/starsem2020/ | 11 | | | MNLP 2020 | Agadir-Essaouira, Morocco | | Jun 28, 2020 | Aug 30, 2020 | Sept 13, 2020 | http://www.ieee.ma/cist20/special-invited-sessions/nlp | 12 | | | INLG2020 | Tokyo, Japan | | May 15, 2020 | July 6, 2020 | August 3, 2020 | http://www.inlg2020.org | 13 | | | SemDial 2020（WatchDial） | Brandeis University | | May 5, 2020 | June 9, 2020 | July 5, 2020 | https://www.brandeis.edu/nasslli2020/semdial.html | 14 | | | NLPCC 2020 | 河南 | | May 15, 2020 | July 30, 2020 | | http://tcci.ccf.org.cn/conference/2020/ | 15 | | | EMNLP 2020 | online | | June 1, 2020 | September 14, 2020 | | https://2020.emnlp.org/ | 16 | | | AACL-IJCNLP 2020 | 苏州 | | June 26, 2020 | Sept 11, 2020 | Sept 30, 2020 | http://www.aacl2020.org/ | 17 | | | NeurIPS 2020 | Vancouver，CANADA | May 5, 2020 | May 12, 2020 | | October 22, 2020 | https://nips.cc | 18 | | | CIKM 2020 | online | April 24, 2020 | May 1, 2020 | July 3, 2020 | August 14th 2020 | https://cikm2020.org/ | 19 | | | CCKS 2020 | 南昌 | | May 21, 2020 | July 1, 2020 | July 15, 2020 | http://sigkg.cn/ccks2020/ | 20 | | | 已结束投稿 | | | | | | | 21 | | | ICML 2020 | Vienna, Austria | Jan 31, 2020 | Feb 7, 2020 | May 9, 2020 | | https://icml.cc/ | 22 | | | IJCAI 2020 | Yokohama, Japan | January 15th, 2020 | January 21, 2020 | April 19, 2020 | | https://ijcai20.org/ | 23 | | | IREC 2020 | Hammamet. Tunisia | January 6th, 2020 | | February 9th, 2020 | February 20th, 2020 | https://irec-conference.com/ | 24 | | | ECNLP-2 @ WWW 2020 | Taipei | | Jan 27, 2020 | Feb 6, 2020 | Feb 15, 2020 | https://sites.google.com/view/ecnlp/www-2020 | 25 | | | CAIR 2020 | Vancouver, Canada | | Jan 10, 2020 | Jan 24, 2020 | Feb 14, 2020 | https://sites.google.com/view/cair-ws/cair-2020 | 26 | | | SIGDIAL 2020 | Boise, Idaho, USA | | Mar 6, 2020 | Apr 26, 2020 | May 11, 2020 | http://www.sigdial.org/workshops/conference21/ | 27 | | | ICIAI 2020 | Xiamen, China | January 10, 2020 | January 5, 2020 | | March 20, 2020 | http://www.iciai.org | 28 | | | AAAI 2020 | Hilton New York Midtown, New York, USA | August 30, 2019 | September 5, 2019 | November 10, 2019 | | https://aaai.org/Conferences/AAAI-20/ | 29 | | | WSDM 2020 | Houston, Texas, USA | August 12, 2019 | August 16, 2019 | October 12, 2019 | | http://www.wsdm-conference.org/2020/ | 30 | | | ACL 2020 | online | | January 31, 2020 | April 3, 2020 | May 1, 2020 | https://acl2020.org/ | 31 | | | IJCAI-PRICAI 2020 | Yokohama, Japan | January 15, 2020 | January 21, 2020 | April 19, 2020 | | http://www.ijcai20.org/ | 32 | 33 | 34 | 35 | ## 参考网站 36 | 37 | [http://www.wikicfp.com](http://www.wikicfp.com/) 38 | 39 | https://aideadlin.es/?sub=NLP 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | 49 | 50 | 51 | --------------------------------------------------------------------------------