diff --git a/README.md b/README.md index 7b779d5..646cbca 100644 --- a/README.md +++ b/README.md @@ -10,188 +10,188 @@ A paper doesn't have to be a peer-reviewed conference/journal paper to appear he ## Machine Learning -* Avrim Blum and Tom Mitchell: Combining Labeled and Unlabeled Data with Co-Training, 1998. +* [Avrim Blum and Tom Mitchell: Combining Labeled and Unlabeled Data with Co-Training, 1998.](https://www.cs.cmu.edu/~avrim/Papers/cotrain.pdf) -* John Lafferty, Andrew McCallum, Fernando C.N. Pereira: Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data, ICML 2001. +* [John Lafferty, Andrew McCallum, Fernando C.N. Pereira: Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data, ICML 2001.](https://repository.upenn.edu/cgi/viewcontent.cgi?article=1162&context=cis_papers) -* Charles Sutton, Andrew McCallum. An Introduction to Conditional Random Fields for Relational Learning. +* [Charles Sutton, Andrew McCallum. An Introduction to Conditional Random Fields for Relational Learning.](https://people.cs.umass.edu/~mccallum/papers/crf-tutorial.pdf) -* Kamal Nigam, et al.: Text Classification from Labeled and Unlabeled Documents using EM. Machine Learning, 1999. +* [Kamal Nigam, et al.: Text Classification from Labeled and Unlabeled Documents using EM. Machine Learning, 1999.](https://www.ri.cmu.edu/pub_files/pub1/nigam_k_1999_1/nigam_k_1999_1.pdf) -* Kevin Knight: Bayesian Inference with Tears, 2009. +* [Kevin Knight: Bayesian Inference with Tears, 2009.](https://www.socsci.uci.edu/~lpearl/courses/readings/Knight2009_BayesWithTears.pdf) -* Marco Tulio Ribeiro et al.: "Why Should I Trust You?": Explaining the Predictions of Any Classifier, KDD 2016. +* [Marco Tulio Ribeiro et al.: "Why Should I Trust You?": Explaining the Predictions of Any Classifier, KDD 2016.](https://arxiv.org/pdf/1602.04938.pdf) -* Marco Tulio Ribeiro et al.: [Beyond Accuracy: Behavioral Testing of NLP Models with CheckList](https://www.aclweb.org/anthology/2020.acl-main.442/), ACL 2020. +* [Marco Tulio Ribeiro et al.: Beyond Accuracy: Behavioral Testing of NLP Models with CheckList](https://aclanthology.org/2020.acl-main.442.pdf) ## Neural Models -* Richard Socher, et al.: Dynamic Pooling and Unfolding Recursive Autoencoders for Paraphrase Detection, NIPS 2011. +* [Richard Socher, et al.: Dynamic Pooling and Unfolding Recursive Autoencoders for Paraphrase Detection, NIPS 2011.](https://papers.nips.cc/paper/2011/file/3335881e06d4d23091389226225e17c7-Paper.pdf) -* Ronan Collobert et al.: Natural Language Processing (almost) from Scratch, J. of Machine Learning Research, 2011. +* [Ronan Collobert et al.: Natural Language Processing (almost) from Scratch, J. of Machine Learning Research, 2011.](https://www.jmlr.org/papers/volume12/collobert11a/collobert11a.pdf) -* Richard Socher, et al.: Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank, EMNLP 2013. +* [Richard Socher, et al.: Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank, EMNLP 2013.](https://aclanthology.org/D13-1170.pdf) -* Xiang Zhang, Junbo Zhao, and Yann LeCun: Character-level Convolutional Networks for Text Classification, NIPS 2015. +* [Xiang Zhang, Junbo Zhao, and Yann LeCun: Character-level Convolutional Networks for Text Classification, NIPS 2015.](https://proceedings.neurips.cc/paper/2015/file/250cf8b51c773f3f8dc8b4be867a9a02-Paper.pdf) -* Yoon Kim: Convolutional Neural Networks for Sentence Classification, 2014. +* [Yoon Kim: Convolutional Neural Networks for Sentence Classification, 2014.](https://arxiv.org/pdf/1408.5882.pdf) -* Christopher Olah: Understanding LSTM Networks, 2015. +* [Christopher Olah: Understanding LSTM Networks, 2015.](https://colah.github.io/posts/2015-08-Understanding-LSTMs/) -* Matthew E. Peters, et al.: Deep contextualized word representations, 2018. +* [Matthew E. Peters, et al.: Deep contextualized word representations, 2018.](https://arxiv.org/pdf/1802.05365.pdf) -* Jacob Devlin, et al.: BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding, 2018. +* [Jacob Devlin, et al.: BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding, 2018.](https://arxiv.org/pdf/1810.04805.pdf) -* Yihan Liu et al. [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://arxiv.org/abs/1907.11692), 2020. +* [Yihan Liu et al. RoBERTa: A Robustly Optimized BERT Pretraining Approach, 2020.](https://arxiv.org/abs/1907.11692) ## Clustering & Word/Sentence Embeddings -* Peter F Brown, et al.: Class-Based n-gram Models of Natural Language, 1992. +* [Peter F Brown, et al.: Class-Based n-gram Models of Natural Language, 1992.](https://www.cs.cmu.edu/~roni/11761/PreviousYearsHandouts/classlm.pdf) -* Tomas Mikolov, et al.: Efficient Estimation of Word Representations in Vector Space, 2013. +* [Tomas Mikolov, et al.: Efficient Estimation of Word Representations in Vector Space, 2013.](https://arxiv.org/pdf/1301.3781.pdf) -* Tomas Mikolov, et al.: Distributed Representations of Words and Phrases and their Compositionality, NIPS 2013. +* [Tomas Mikolov, et al.: Distributed Representations of Words and Phrases and their Compositionality, NIPS 2013.](https://proceedings.neurips.cc/paper/2013/file/9aa42b31882ec039965f3c4923ce901b-Paper.pdf) -* Quoc V. Le and Tomas Mikolov: Distributed Representations of Sentences and Documents, 2014. +* [Quoc V. Le and Tomas Mikolov: Distributed Representations of Sentences and Documents, 2014.](https://arxiv.org/pdf/1405.4053.pdf) -* Jeffrey Pennington, et al.: GloVe: Global Vectors for Word Representation, 2014. +* [Jeffrey Pennington, et al.: GloVe: Global Vectors for Word Representation, 2014.](https://aclanthology.org/D14-1162.pdf) -* Ryan Kiros, et al.: Skip-Thought Vectors, 2015. +* [Ryan Kiros, et al.: Skip-Thought Vectors, 2015.](https://arxiv.org/pdf/1506.06726.pdf) -* Piotr Bojanowski, et al.: Enriching Word Vectors with Subword Information, 2017. +* [Piotr Bojanowski, et al.: Enriching Word Vectors with Subword Information, 2017.](https://arxiv.org/pdf/1607.04606.pdf) -* Daniel Cer et al.: [Universal Sentence Encoder](https://arxiv.org/abs/1803.11175), 2018. +* [Daniel Cer et al.: Universal Sentence Encoder, 2018.](https://arxiv.org/abs/1803.11175) ## Topic Models -* Thomas Hofmann: Probabilistic Latent Semantic Indexing, SIGIR 1999. +* [Thomas Hofmann: Probabilistic Latent Semantic Indexing, SIGIR 1999.](https://sigir.org/wp-content/uploads/2017/06/p211.pdf) -* David Blei, Andrew Y. Ng, and Michael I. Jordan: Latent Dirichlet Allocation, J. Machine Learning Research, 2003. +* [David Blei, Andrew Y. Ng, and Michael I. Jordan: Latent Dirichlet Allocation, J. Machine Learning Research, 2003.](https://www.jmlr.org/papers/volume3/blei03a/blei03a.pdf) ## Language Modeling -* Joshua Goodman: A bit of progress in language modeling, MSR Technical Report, 2001. +* [Joshua Goodman: A bit of progress in language modeling, MSR Technical Report, 2001.](https://arxiv.org/pdf/cs/0108005.pdf) -* Stanley F. Chen and Joshua Goodman: An Empirical Study of Smoothing Techniques for Language Modeling, ACL 2006. +* [Stanley F. Chen and Joshua Goodman: An Empirical Study of Smoothing Techniques for Language Modeling, ACL 2006.](https://dash.harvard.edu/bitstream/handle/1/25104739/tr-10-98.pdf;jsessionid=0F01586D4D238B2EC40A63094F9B50FC?sequence=1) -* Yee Whye Teh: A Hierarchical Bayesian Language Model based on Pitman-Yor Processes, COLING/ACL 2006. +* [Yee Whye Teh: A Hierarchical Bayesian Language Model based on Pitman-Yor Processes, COLING/ACL 2006.](http://www.gatsby.ucl.ac.uk/~ywteh/research/compling/acl2006.pdf) -* Yee Whye Teh: A Bayesian interpretation of Interpolated Kneser-Ney, 2006. +* [Yee Whye Teh: A Bayesian interpretation of Interpolated Kneser-Ney, 2006.](https://www.stats.ox.ac.uk/~teh/research/compling/hpylm.pdf) -* Yoshua Bengio, et al.: A Neural Probabilistic Language Model, J. of Machine Learning Research, 2003. +* [Yoshua Bengio, et al.: A Neural Probabilistic Language Model, J. of Machine Learning Research, 2003.](https://www.jmlr.org/papers/volume3/bengio03a/bengio03a.pdf) -* Andrej Karpathy: The Unreasonable Effectiveness of Recurrent Neural Networks, 2015. +* [Andrej Karpathy: The Unreasonable Effectiveness of Recurrent Neural Networks, 2015.](https://web.stanford.edu/class/cs379c/archive/2018/class_messages_listing/content/Artificial_Neural_Network_Technology_Tutorials/KarparthyUNREASONABLY-EFFECTIVE-RNN-15.pdf) -* Yoon Kim, et al.: Character-Aware Neural Language Models, 2015. +* [Yoon Kim, et al.: Character-Aware Neural Language Models, 2015.](https://arxiv.org/pdf/1508.06615.pdf) -* Alec Radford, et al.: [Language Models are Unsupervised Multitask Learners](https://d4mucfpksywv.cloudfront.net/better-language-models/language_models_are_unsupervised_multitask_learners.pdf), 2018. +* [Alec Radford, et al.: Language Models are Unsupervised Multitask Learners, 2018.](https://d4mucfpksywv.cloudfront.net/better-language-models/language_models_are_unsupervised_multitask_learners.pdf) ## Segmentation, Tagging, Parsing -* Donald Hindle and Mats Rooth. Structural Ambiguity and Lexical Relations, Computational Linguistics, 1993. +* [Donald Hindle and Mats Rooth. Structural Ambiguity and Lexical Relations, Computational Linguistics, 1993.](https://aclanthology.org/J93-1005.pdf) -* Adwait Ratnaparkhi: A Maximum Entropy Model for Part-Of-Speech Tagging, EMNLP 1996. +* [Adwait Ratnaparkhi: A Maximum Entropy Model for Part-Of-Speech Tagging, EMNLP 1996.](https://aclanthology.org/W96-0213.pdf) -* Eugene Charniak: A Maximum-Entropy-Inspired Parser, NAACL 2000. +* [Eugene Charniak: A Maximum-Entropy-Inspired Parser, NAACL 2000.](https://www.ling.upenn.edu/courses/cogs502/CharniakNAACL2000.pdf) -* Michael Collins: Discriminative Training Methods for Hidden Markov Models: Theory and Experiments with Perceptron Algorithms, EMNLP 2002. +* [Michael Collins: Discriminative Training Methods for Hidden Markov Models: Theory and Experiments with Perceptron Algorithms, EMNLP 2002.](https://aclanthology.org/W02-1001.pdf) -* Dan Klein and Christopher Manning: Accurate Unlexicalized Parsing, ACL 2003. +* [Dan Klein and Christopher Manning: Accurate Unlexicalized Parsing, ACL 2003.](https://nlp.stanford.edu/~manning/papers/unlexicalized-parsing.pdf) -* Dan Klein and Christopher Manning: Corpus-Based Induction of Syntactic Structure: Models of Dependency and Constituency, ACL 2004. +* [Dan Klein and Christopher Manning: Corpus-Based Induction of Syntactic Structure: Models of Dependency and Constituency, ACL 2004.](https://aclanthology.org/P04-1061.pdf) -* Joakim Nivre and Mario Scholz: Deterministic Dependency Parsing of English Text, COLING 2004. +* [Joakim Nivre and Mario Scholz: Deterministic Dependency Parsing of English Text, COLING 2004.](https://aclanthology.org/C04-1010.pdf) -* Ryan McDonald et al.: Non-Projective Dependency Parsing using Spanning-Tree Algorithms, EMNLP 2005. +* [Ryan McDonald et al.: Non-Projective Dependency Parsing using Spanning-Tree Algorithms, EMNLP 2005.](https://aclanthology.org/H05-1066.pdf) -* Daniel Andor et al.: Globally Normalized Transition-Based Neural Networks, 2016. +* [Daniel Andor et al.: Globally Normalized Transition-Based Neural Networks, 2016.](https://arxiv.org/pdf/1603.06042.pdf) -* Oriol Vinyals, et al.: Grammar as a Foreign Language, 2015. +* [Oriol Vinyals, et al.: Grammar as a Foreign Language, 2015.](https://proceedings.neurips.cc/paper/2015/file/277281aada22045c03945dcb2ca6f2ec-Paper.pdf) ## Sequential Labeling & Information Extraction -* Marti A. Hearst: Automatic Acquisition of Hyponyms from Large Text Corpora, COLING 1992. +* [Marti A. Hearst: Automatic Acquisition of Hyponyms from Large Text Corpora, COLING 1992.](https://aclanthology.org/C92-2082.pdf) -* Collins and Singer: Unsupervised Models for Named Entity Classification, EMNLP 1999. +* [Collins and Singer: Unsupervised Models for Named Entity Classification, EMNLP 1999.](https://aclanthology.org/W99-0613.pdf) -* Patrick Pantel and Dekang Lin, Discovering Word Senses from Text, SIGKDD, 2002. +* [Patrick Pantel and Dekang Lin, Discovering Word Senses from Text, SIGKDD, 2002.](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.130.6056&rep=rep1&type=pdf) -* Mike Mintz et al.: Distant supervision for relation extraction without labeled data, ACL 2009. +* [Mike Mintz et al.: Distant supervision for relation extraction without labeled data, ACL 2009.](https://aclanthology.org/P09-1113.pdf) -* Zhiheng Huang et al.: Bidirectional LSTM-CRF Models for Sequence Tagging, 2015. +* [Zhiheng Huang et al.: Bidirectional LSTM-CRF Models for Sequence Tagging, 2015.](https://arxiv.org/pdf/1508.01991.pdf) -* Xuezhe Ma and Eduard Hovy: End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF, ACL 2016. +* [Xuezhe Ma and Eduard Hovy: End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF, ACL 2016.](https://arxiv.org/pdf/1603.01354.pdf) ## Machine Translation & Transliteration, Sequence-to-Sequence Models -* Peter F. Brown et al.: A Statistical Approach to Machine Translation, Computational Linguistics, 1990. +* [Peter F. Brown et al.: A Statistical Approach to Machine Translation, Computational Linguistics, 1990.](https://aclanthology.org/J90-2002.pdf) -* Kevin Knight, Graehl Jonathan. Machine Transliteration. Computational Linguistics, 1992. +* [Kevin Knight, Graehl Jonathan. Machine Transliteration. Computational Linguistics, 1992.](https://aclanthology.org/J98-4003.pdf) -* Dekai Wu: Inversion Transduction Grammars and the Bilingual Parsing of Parallel Corpora, Computational Linguistics, 1997. +* [Dekai Wu: Inversion Transduction Grammars and the Bilingual Parsing of Parallel Corpora, Computational Linguistics, 1997.](https://aclanthology.org/J97-3002.pdf) -* Kevin Knight: A Statistical MT Tutorial Workbook, 1999. +* [Kevin Knight: A Statistical MT Tutorial Workbook, 1999.](https://www.cis.uni-muenchen.de/~fraser/readinggroup/knight_1999_TUTORIAL_model3.pdf) -* Kishore Papineni, et al.: BLEU: a Method for Automatic Evaluation of Machine Translation, ACL 2002. +* [Kishore Papineni, et al.: BLEU: a Method for Automatic Evaluation of Machine Translation, ACL 2002.](https://aclanthology.org/P02-1040.pdf) -* Philipp Koehn, Franz J Och, and Daniel Marcu: Statistical Phrase-Based Translation, NAACL 2003. +* [Philipp Koehn, Franz J Och, and Daniel Marcu: Statistical Phrase-Based Translation, NAACL 2003.](https://aclanthology.org/N03-1017.pdf) -* Philip Resnik and Noah A. Smith: The Web as a Parallel Corpus, Computational Linguistics, 2003. +* [Philip Resnik and Noah A. Smith: The Web as a Parallel Corpus, Computational Linguistics, 2003.](https://aclanthology.org/J03-3002.pdf) -* Franz J Och and Hermann Ney: The Alignment-Template Approach to Statistical Machine Translation, Computational Linguistics, 2004. +* [Franz J Och and Hermann Ney: The Alignment-Template Approach to Statistical Machine Translation, Computational Linguistics, 2004.](https://aclanthology.org/J04-4002.pdf) -* David Chiang. A Hierarchical Phrase-Based Model for Statistical Machine Translation, ACL 2005. +* [David Chiang. A Hierarchical Phrase-Based Model for Statistical Machine Translation, ACL 2005.](https://aclanthology.org/P05-1033.pdf) -* Ilya Sutskever, Oriol Vinyals, and Quoc V. Le: Sequence to Sequence Learning with Neural Networks, NIPS 2014. +* [Ilya Sutskever, Oriol Vinyals, and Quoc V. Le: Sequence to Sequence Learning with Neural Networks, NIPS 2014.](https://papers.nips.cc/paper/2014/file/a14ac55a4f27472c5d894ec1c3c743d2-Paper.pdf) -* Oriol Vinyals, Quoc Le: A Neural Conversation Model, 2015. +* [Oriol Vinyals, Quoc Le: A Neural Conversation Model, 2015.](https://arxiv.org/pdf/1506.05869.pdf) -* Dzmitry Bahdanau, et al.: Neural Machine Translation by Jointly Learning to Align and Translate, 2014. +* [Dzmitry Bahdanau, et al.: Neural Machine Translation by Jointly Learning to Align and Translate, 2014.](https://arxiv.org/pdf/1409.0473.pdf) -* Minh-Thang Luong, et al.: Effective Approaches to Attention-based Neural Machine Translation, 2015. +* [Minh-Thang Luong, et al.: Effective Approaches to Attention-based Neural Machine Translation, 2015.](https://arxiv.org/pdf/1508.04025.pdf) -* Rico Sennrich et al.: Neural Machine Translation of Rare Words with Subword Units. ACL 2016. +* [Rico Sennrich et al.: Neural Machine Translation of Rare Words with Subword Units. ACL 2016.](https://arxiv.org/pdf/1508.07909.pdf) -* Yonghui Wu, et al.: Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation, 2016. +* [Yonghui Wu, et al.: Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation, 2016.](https://arxiv.org/pdf/1609.08144.pdf) -* Melvin Johnson, et al.: [Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation](https://arxiv.org/abs/1611.04558), 2016. +* [Melvin Johnson, et al.: Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation, 2016.](https://arxiv.org/abs/1611.04558) -* Jonas Gehring, et al.: Convolutional Sequence to Sequence Learning, 2017. +* [Jonas Gehring, et al.: Convolutional Sequence to Sequence Learning, 2017.](https://arxiv.org/pdf/1705.03122.pdf) -* Ashish Vaswani, et al.: Attention Is All You Need, 2017. +* [Ashish Vaswani, et al.: Attention Is All You Need, 2017.](https://arxiv.org/pdf/1706.03762.pdf) ## Coreference Resolution -* Vincent Ng: Supervised Noun Phrase Coreference Research: The First Fifteen Years, ACL 2010. +* [Vincent Ng: Supervised Noun Phrase Coreference Research: The First Fifteen Years, ACL 2010.](https://aclanthology.org/P10-1142.pdf) -* Kenton Lee at al.: End-to-end Neural Coreference Resolution, EMNLP 2017. +* [Kenton Lee at al.: End-to-end Neural Coreference Resolution, EMNLP 2017.](https://arxiv.org/pdf/1707.07045.pdf) ## Automatic Text Summarization * Kevin Knight and Daniel Marcu: Summarization beyond sentence extraction. Artificial Intelligence 139, 2002. -* James Clarke and Mirella Lapata: Modeling Compression with Discourse Constraints. EMNLP-CONLL 2007. +* [James Clarke and Mirella Lapata: Modeling Compression with Discourse Constraints. EMNLP-CONLL 2007.](https://aclanthology.org/D07-1001.pdf) -* Ryan McDonald: A Study of Global Inference Algorithms in Multi-Document Summarization, ECIR 2007. +* [Ryan McDonald: A Study of Global Inference Algorithms in Multi-Document Summarization, ECIR 2007.](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.94.4583&rep=rep1&type=pdf) -* Wen-tau Yih et al.: Multi-Document Summarization by Maximizing Informative Content-Words. IJCAI 2007. +* [Wen-tau Yih et al.: Multi-Document Summarization by Maximizing Informative Content-Words. IJCAI 2007.](https://www.ijcai.org/Proceedings/07/Papers/287.pdf) -* Alexander M Rush, et al.: A Neural Attention Model for Sentence Summarization. EMNLP 2015. +* [Alexander M Rush, et al.: A Neural Attention Model for Sentence Summarization. EMNLP 2015.](https://aclanthology.org/D15-1044.pdf) -* Abigail See et al.: [Get To The Point: Summarization with Pointer-Generator Networks](https://www.aclweb.org/anthology/P17-1099/). ACL 2017. +* [Abigail See et al.: Get To The Point: Summarization with Pointer-Generator Networks. ACL 2017. ](https://www.aclweb.org/anthology/P17-1099/) ## Question Answering and Machine Comprehension -* Pranav Rajpurkar et al.: SQuAD: 100,000+ Questions for Machine Comprehension of Text. EMNLP 2015. +* [Pranav Rajpurkar et al.: SQuAD: 100,000+ Questions for Machine Comprehension of Text. EMNLP 2015.](https://arxiv.org/pdf/1606.05250.pdf) -* Minjoon Soo et al.: Bi-Directional Attention Flow for Machine Comprehension. ICLR 2015. +* [Minjoon Soo et al.: Bi-Directional Attention Flow for Machine Comprehension. ICLR 2015.](https://arxiv.org/pdf/1611.01603.pdf) ## Generation, Reinforcement Learning -* Jiwei Li, et al.: Deep Reinforcement Learning for Dialogue Generation, EMNLP 2016. +* [Jiwei Li, et al.: Deep Reinforcement Learning for Dialogue Generation, EMNLP 2016.](https://arxiv.org/pdf/1606.01541.pdf) -* Marc’Aurelio Ranzato et al.: Sequence Level Training with Recurrent Neural Networks. ICLR 2016. +* [Marc’Aurelio Ranzato et al.: Sequence Level Training with Recurrent Neural Networks. ICLR 2016.](https://arxiv.org/pdf/1511.06732.pdf) -* Samuel R Bowman et al.: [Generating sentences from a continuous space](https://www.aclweb.org/anthology/K16-1002/), CoNLL 2016. +* [Samuel R Bowman et al.: Generating sentences from a continuous space, CoNLL 2016.](https://www.aclweb.org/anthology/K16-1002/) -* Lantao Yu, et al.: SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient, AAAI 2017. +* [Lantao Yu, et al.: SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient, AAAI 2017.](https://www.aaai.org/Conferences/AAAI/2017/PreliminaryPapers/12-Yu-L-14344.pdf)