【论文整理】100 篇自然语言处理必读论文！涵盖主流研究方向！
100 篇自然语言处理必读论文
聚类&词向量
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Peter F Brown, et al.: Class-Based n-gram Models of Natural Language, 1992.
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Tomas Mikolov, et al.: Efficient Estimation of Word Representations in Vector Space, 2013.
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Tomas Mikolov, et al.: Distributed Representations of Words and Phrases and their Compositionality, NIPS 2013.
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Quoc V. Le and Tomas Mikolov: Distributed Representations of Sentences and Documents, 2014.
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Jeffrey Pennington, et al.: GloVe: Global Vectors for Word Representation, 2014.
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Ryan Kiros, et al.: Skip-Thought Vectors, 2015.
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Piotr Bojanowski, et al.: Enriching Word Vectors with Subword Information, 2017.
主题模型
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Thomas Hofmann: Probabilistic Latent Semantic Indexing, SIGIR 1999.
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David Blei, Andrew Y. Ng, and Michael I. Jordan: Latent Dirichlet Allocation, J. Machine Learning Research, 2003.
语言模型
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Joshua Goodman: A bit of progress in language modeling, MSR Technical Report, 2001.
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Stanley F. Chen and Joshua Goodman: An Empirical Study of Smoothing Techniques for Language Modeling, ACL 2006.
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Yee Whye Teh: A Hierarchical Bayesian Language Model based on Pitman-Yor Processes, COLING/ACL 2006.
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Yee Whye Teh: A Bayesian interpretation of Interpolated Kneser-Ney, 2006.
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Yoshua Bengio, et al.: A Neural Probabilistic Language Model, J. of Machine Learning Research, 2003.
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Andrej Karpathy: The Unreasonable Effectiveness of Recurrent Neural Networks, 2015.
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Yoon Kim, et al.: Character-Aware Neural Language Models, 2015.
分割、标注、解析
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Donald Hindle and Mats Rooth. Structural Ambiguity and Lexical Relations, Computational Linguistics, 1993.
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Adwait Ratnaparkhi: A Maximum Entropy Model for Part-Of-Speech Tagging, EMNLP 1996.
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Eugene Charniak: A Maximum-Entropy-Inspired Parser, NAACL 2000.
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Michael Collins: Discriminative Training Methods for Hidden Markov Models: Theory and Experiments with Perceptron Algorithms, EMNLP 2002.
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Dan Klein and Christopher Manning: Accurate Unlexicalized Parsing, ACL 2003.
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Dan Klein and Christopher Manning: Corpus-Based Induction of Syntactic Structure: Models of Dependency and Constituency, ACL 2004.
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Joakim Nivre and Mario Scholz: Deterministic Dependency Parsing of English Text, COLING 2004.
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Ryan McDonald et al.: Non-Projective Dependency Parsing using Spanning-Tree Algorithms, EMNLP 2005.
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Daniel Andor et al.: Globally Normalized Transition-Based Neural Networks, 2016.
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Oriol Vinyals, et al.: Grammar as a Foreign Language, 2015.
序列模型、信息抽取
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Marti A. Hearst: Automatic Acquisition of Hyponyms from Large Text Corpora, COLING 1992.
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Collins and Singer: Unsupervised Models for Named Entity Classification, EMNLP 1999.
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Patrick Pantel and Dekang Lin, Discovering Word Senses from Text, SIGKDD, 2002.
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Mike Mintz et al.: Distant supervision for relation extraction without labeled data, ACL 2009.
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Zhiheng Huang et al.: Bidirectional LSTM-CRF Models for Sequence Tagging, 2015.
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Xuezhe Ma and Eduard Hovy: End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF, ACL 2016.
机器翻译， seq2seq模型
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Peter F. Brown et al.: A Statistical Approach to Machine Translation, Computational Linguistics, 1990.
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Kevin Knight, Graehl Jonathan. Machine Transliteration. Computational Linguistics, 1992.
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Dekai Wu: Inversion Transduction Grammars and the Bilingual Parsing of Parallel Corpora, Computational Linguistics, 1997.
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Kevin Knight: A Statistical MT Tutorial Workbook, 1999.
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Kishore Papineni, et al.: BLEU: a Method for Automatic Evaluation of Machine Translation, ACL 2002.
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Philipp Koehn, Franz J Och, and Daniel Marcu: Statistical Phrase-Based Translation, NAACL 2003.
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Philip Resnik and Noah A. Smith: The Web as a Parallel Corpus, Computational Linguistics, 2003.
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Franz J Och and Hermann Ney: The Alignment-Template Approach to Statistical Machine Translation, Computational Linguistics, 2004.
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David Chiang. A Hierarchical Phrase-Based Model for Statistical Machine Translation, ACL 2005.
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Ilya Sutskever, Oriol Vinyals, and Quoc V. Le: Sequence to Sequence Learning with Neural Networks, NIPS 2014.
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Oriol Vinyals, Quoc Le: A Neural Conversation Model, 2015.
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Dzmitry Bahdanau, et al.: Neural Machine Translation by Jointly Learning to Align and Translate, 2014.
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Minh-Thang Luong, et al.: Effective Approaches to Attention-based Neural Machine Translation, 2015.
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Rico Sennrich et al.: Neural Machine Translation of Rare Words with Subword Units. ACL 2016.
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Yonghui Wu, et al.: Google’s Neural Machine Translation System: Bridging the Gap between Human and Machine Translation, 2016.
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Jonas Gehring, et al.: Convolutional Sequence to Sequence Learning, 2017.
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Ashish Vaswani, et al.: Attention Is All You Need, 2017.
指代消歧
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Vincent Ng: Supervised Noun Phrase Coreference Research: The First Fifteen Years, ACL 2010.
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Kenton Lee at al.: End-to-end Neural Coreference Resolution, EMNLP 2017.
自动文本总结
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Kevin Knight and Daniel Marcu: Summarization beyond sentence extraction. Artificial Intelligence 139, 2002.
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James Clarke and Mirella Lapata: Modeling Compression with Discourse Constraints. EMNLP-CONLL 2007.
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Ryan McDonald: A Study of Global Inference Algorithms in Multi-Document Summarization, ECIR 2007.
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Wen-tau Yih et al.: Multi-Document Summarization by Maximizing Informative Content-Words. IJCAI 2007.
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Alexander M Rush, et al.: A Neural Attention Model for Sentence Summarization. EMNLP 2015.
问答系统、阅读理解
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Pranav Rajpurkar et al.: SQuAD: 100,000+ Questions for Machine Comprehension of Text. EMNLP 2015.
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Minjoon Soo et al.: Bi-Directional Attention Flow for Machine Comprehension. ICLR 2015.
生成模型、强化学习
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Jiwei Li, et al.: Deep Reinforcement Learning for Dialogue Generation, EMNLP 2016.
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Marc’Aurelio Ranzato et al.: Sequence Level Training with Recurrent Neural Networks. ICLR 2016.
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Lantao Yu, et al.: SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient, AAAI 2017.
机器学习
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Avrim Blum and Tom Mitchell: Combining Labeled and Unlabeled Data with Co-Training, 1998.
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John Lafferty, Andrew McCallum, Fernando C.N. Pereira: Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data, ICML 2001.
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Charles Sutton, Andrew McCallum. An Introduction to Conditional Random Fields for Relational Learning.
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Kamal Nigam, et al.: Text Classification from Labeled and Unlabeled Documents using EM. Machine Learning, 1999.
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Kevin Knight: Bayesian Inference with Tears, 2009.
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Marco Tulio Ribeiro et al.: “Why Should I Trust You?”: Explaining the Predictions of Any Classifier, KDD 2016.
神经网络模型
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Richard Socher, et al.: Dynamic Pooling and Unfolding Recursive Autoencoders for Paraphrase Detection, NIPS 2011.
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Ronan Collobert et al.: Natural Language Processing (almost) from Scratch, J. of Machine Learning Research, 2011.
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Richard Socher, et al.: Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank, EMNLP 2013.
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Xiang Zhang, Junbo Zhao, and Yann LeCun: Character-level Convolutional Networks for Text Classification, NIPS 2015.
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Yoon Kim: Convolutional Neural Networks for Sentence Classification, 2014.
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Christopher Olah: Understanding LSTM Networks, 2015.
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Matthew E. Peters, et al.: Deep contextualized word representations, 2018.
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Jacob Devlin, et al.: BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding, 2018.