SIG Discourse【談話研究会 / 2017】

Special Interest Group on Discourse (SIG Discourse) discusses interesting findings of past/state-of-the-art researches. We also report and discuss research progress of our member. Typically, we read one paper (30 minutes) and discuss research progress of one person (40 minutes) at a time. The schedule is listed below.

Date

• 1st Semester: Thu 16:20-17:50
• 2nd Semester: Thu 14:40-16:10

Members

乾, 岡﨑, 井之上, Paul, 稲田, 横井, 高橋, 佐藤, 清野, 赤間, 白井, 栗林

Related Keywords

人工知能/Artificial Intelligence，物語理解/Story Understanding，プラン/Plan，修辞構造/Rhetorical Structure，照応/Anaphora，省略/Ellipsis，ゼロ照応/Zero Anaphora

Policy

• KIAI との役割分担
  • 談話: paper reading（サーベイ結果や自分の研究を紹介してもOK）
  • KIAI: 進捗報告
• 読みかた
  • 各回2名が発表
  • だいたい1ヶ月に1度当番が回ってくる
  • 忙しければ 自由に 延期
  • 発表前に読む論文を #random で紹介
• 聞きかた
  • 各回1度は質問・コメントをする

Schedule

Future

Upcoming

• Thu 3/8 14:40- ＊今年度ラスト(?)
  • 高橋
    • 特集：KBC の闇
    • D. Q. Nguyen. An overview of embedding models of entities and relationships for knowledge base completion. arXiv, 2018.
    • arXiv, annotated paper

Done

• Thu 2/15 14:40-

• 清野
  • Philipp Koehn and Rebecca Knowles. Six challenges for neural machine translation. In Proceedings of the First Workshop on Neural Machine Translation, pp. 28–39, Vancouver, August 2017. Association for Computational Linguistics.
  • 内部資料
  • Elliott, Desmond, and Akos Kádár. “Imagination improves multimodal translation.” arXiv preprint arXiv:1705.04350 (2017).

• Thu 2/8 10:30-

• 栗林

Wachsmuth, H. et al. (2017), ‘The Impact of Modeling Overall Argumentation with Tree Kernels’, EMNLP 2017

• annotated paper, 導入
• Paul
• Vu et al. (2017), Lexical-semantic resources: yet powerful resources for automatic personality classification, arXiv
• arXiv, 内部資料

• Thu 2/1 14:40-
  • 横井
    • Jiwei Li+, “A Diversity-Promoting Objective Function for Neural Conversation Models,” NAACL 2016.
    • arXiv, 2016赤間さんスライド, annotated paper
  • 白井
    • Qin, Lianhui, et al. “Adversarial Connective-exploiting Networks for Implicit Discourse Relation Classification.” Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Vol. 1. 2017.
    • Paper, arXiv

• Thu 1/25 14:40- 再開
  • 井之上
    • Han Xiao, Minlie Huang, and Xiaoyan Zhu. From One Point to a Manifold: Knowledge Graph Embedding for Precise Link Prediction. IJCAI2016. paper

• Tue 12/21, 14:40- 年内ラスト
  • 吉成 CEA発表練習

• Thu 12/14, 14:40-
  • 赤間
    • Dict2vec : Learning Word Embeddings using Lexical Dictionaries; Julien Tissier, Christophe Gravier, Amaury Habrard, EMNLP2017 paper memo

• Thu 12/7, 14:40-
  • 栗林
    • Dual Decomposition for Parsing with Non-Projective Head Automata

T. Koo, A. M. Rush, M. Collins, T. Jaakkola, and David Sontag, EMNLP 2010.
paper
author’s slide

• 白井
  • Teng, Zhiyang, Duy-Tin Vo, and Yue Zhang. “Context-Sensitive Lexicon Features for Neural Sentiment Analysis.” EMNLP. 2016. paper 内部資料

• Thu 11/30, 15:40-（開始時刻注意）
  • Paul
    • Habernal et al, 2017. The Argument Reasoning Comprehension Task. Annotated Paper

• Thu 11/21, 13:00-
  • 赤間
    • IJCNLP発表練習（発表8分+質疑2分）
    • 内部資料

• Thu 11/16, 14:40-
  • 井之上
    • Tim Rocktäschel and Sebastian Riedel. End-to-end Differentiable Proving. NIPS2017.
    • paper author’s slides

• Thu 11/9, 14:40-
  • 高橋
    • Kenton Lee, Luheng He, Mike Lewis and Luke Zettlemoyer. “End-to-end Neural Coreference Resolution.” EMNLP. 2017.
    • paper, annotated paper
  • Paul
    • Vlad Niculae, Joonsuk Park, Claire Cardie. “Argument Mining with Structured SVMs and RNNs”. ACL2017
    • Annotated Paper

• Thu 11/2, 14:40-
  • 白井
    • Zhang, Meishan, Yue Zhang, and Duy-Tin Vo. “Gated Neural Networks for Targeted Sentiment Analysis.” AAAI. 2016.
    • paper, annotated paper, introduction
  • 議題：コマ変更（総合研究会かKIAIに合わせる？＆乾さん居る日） → 総合研究会と同曜日になったのでこのまま。KIAIを動かす？
  • 議題：横井延期 → 11/30に

• Thu 10/19, 14:15- （開始時刻注意）
  • 赤間
    • Intrinsic Subspace Evaluation of Word Embedding Representations; Yadollah Yaghoobzadeh and Hinrich Schutze. ACL2016
    • paper memo
  • 栗林
    • Allen Nie, Erin D. Bennett, Noah D. Goodman. “DisSent: Sentence Representation Learning from Explicit Discourse Relations” arXiv, 2017.
    • arXiv, annotated paper,, &handref(2017/disco/disco-20171019-kuribayashi3.pdf,memo(sentence representation));

• Tue 10/10, 13:00-
  • 議題：コマ変更（火曜3限→木曜4限）
  • 横井
    • Kelvin Guu, Tatsunori B. Hashimoto, Yonatan Oren, Percy Liang. “Generating Sentences by Editing Prototypes.” arXiv, 2017.
    • arXiv, annotated paper
  • 高橋
    • Melamud, Oren, Jacob Goldberger, and Ido Dagan. “context2vec: Learning Generic Context Embedding with Bidirectional LSTM.” CoNLL. 2016.
    • paper, annotated paper

• Tue 10/3, 13:00-
  • 栗林 スライド
  • 白井 memo

• Tue 9/26, 14:40-
  • 赤間
    • Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings; Tolga Bolukbasi, Kai-Wei Chang, James Zou, Venkatesh Saligrama, Adam Kalai. NIPS2016
    • paper memo

• Tue 9/19, 14:40-
  • 吉成
    • Liping Wang , Qing Li , Na Li , Guozhu Dong , Yu Yang.“Substructure Similarity Measurement in Chinese Recipes.”Proceedings of the 17th international conference on World Wide Web. ACM, 2008.
    • paper, memo

• 栗林
  • Peter Potash, Alexey Romanov, Anna Rumshisky. Here’s My Point: Joint Pointer Architecture for Argument Mining. EMNLP, 2017.
  • paper, annotated paper, memo

• Tue 9/12, 13:00-
  • 横井
    • Ashutosh Modi, Ivan Titov, Vera Demberg, Asad Sayeed, Manfred Pinkal. “Modeling Semantic Expectation: Using Script Knowledge for Referent Prediction.” TACL, 2017.
    • ACL anthology, annotated paper
  • 高橋
    • Benjamin Heinzerling, Nafise Sadat Moosavi and Michael Strube. “Revisiting Selectional Preferences for Coreference Resolution.” EMNLP, 2017.
    • ACL anthology, annotated paper, memo

• August: Summer Break

• Thu 7/27, 16:50-
  • Paul
    • What is the Essence of a Claim? Cross-domain claim identification – Johannes Daxenberger, Steffen Eger, Ivan Habernal, Christian Stab, Iryna Gurevych
    • 内部資料 Paper
  • 佐藤: 進捗報告 内部資料

• Thu 7/13, 16:20-
  • 清野
    • Learning to Compute Word Embeddings On the Fly – Dzmitry Bahdanau, Tom Bosc, Stanisław Jastrzębski, Edward Grefenstette, Pascal Vincent, Yoshua Bengio
    • 内部資料 Paper

• Thu 7/6, 16:20-
  • 高橋
    • Donahue, Chris, Zachary C. Lipton, and Julian McAuley. “Dance Dance Convolution.” ICLR, 2017.
    • arXiv, annotated paper
    • MIT Technology Review

• Thu 6/29, 16:40-
  • 横井
    • Maximilian Nickel and Douwe Kiela. “Poincaré Embeddings for Learning Hierarchical Representations.” arXiv preprint, 2017.
    • arXiv, annotated paper, memo
  • 稲田
    • Learning to generate one-sentence biographies from Wikidata, Andrew Chisholm et al., EACL2017
    • paper, 内部資料

• Thu 6/22, 16:20-
  • 清野
    • seq2seq+attentionフレームワークの紹介 HTML PDF

• Thu 6/15, 16:20-
  • 赤間
    • Automatic conversion of sentence-end expressions for utterance characterization of dialogue systems; Chiaki Miyazaki, Toru Hirano, Ryuichiro Higashinaka, Toshiro Makino and Yoshihiro Matsuo, PACLIC2015
    • paper memo

• Thu 6/1, 16:20-
  • 横井
    • Ben Athiwaratkun and Andrew Gordon Wilson. “Multimodal Word Distributions.” To appear at ACL 2017.
    • arXiv, GitHub, annotated paper
    • 参考：Luke Vilnis and Andrew McCallum. “Word Representations via Gaussian Embeddings.” ICLR 2015.
    • arXiv, 著者slide, 一昨年の談話資料

• 高橋
  • Nafise Sadat Moosavi and Michael Strube. “Lexical Features in Coreference Resolution: To be Used With Caution.” To appear in ACL 2017
  • arXiv, annotated paper

• Thu 5/25, 16:20-
  • (おやすみ; JSAI)

• Thu 5/18, 16:20-
  • Paul
    • Recognizing Insufficiently Supported Arguments in Argumentative Essays; Stab & Gurevych, EACL2017
    • 内部資料

• Fri 5/12, 17:30- (after the weekly research seminar)
  • 清野
    • Get To The Point: Summarization with Pointer-Generator Networks; Abigail See+, To appear in ACL 2017
    • Paper, メモ, 著者によるブログ記事

• Tue 4/25, 16:20-
  • 赤間
    • Controlling Politeness in Neural Machine Translation via Side Constraints; Rico Sennrich+, NAACL2016
    • paper memo
  • 稲田
    • Fandong Meng et.al., Interactive Attention for Neural Machine Translation, COLING, 2016
    • paper 内部資料

• Tue 4/18, 16:20-
  • 横井
    • S. Zhao, et al. “Constructing and embedding abstract event causality networks from text snippets.” WSDM, 2017.
    • ACM, annotated paper
  • 高橋
    • Liua, Quan, et al. “Commonsense Knowledge Enhanced Embeddings for Solving Pronoun Disambiguation Problems in Winograd Schema Challenge.” arXiv preprint arXiv:1611.04146 (2016).
    • arXiv, annotated paper, memo

• Wed 4/12, 13:00-
  • 談話研究会の特徴(横井), &handref(2017/disco/disco-20170412-kickoff2.pdf,談話研究会の興味(井之上さんスライド));
  • 研究紹介
    • Paul: 内部資料
    • 横井: 関係知識とセグメンテーション 内部資料
    • 高橋: 文脈を理解したい 内部資料
    • 清野: 内部資料
    • 赤間: 内部資料
    • 稲田: 内部資料

Assignment

• v: presented
• (v): assigned

後期

前期

Past

• Spring 2016-Winter 2017
• Spring 2015-Winter 2016
• Spring 2014-Winter 2015
• Spring 2013-Winter 2014
• Spring 2012-Winter 2013
• Spring 2011-Winter 2012
• Spring 2010-Winter 2011

Links

Artificial Intelligence

• Levesque, Hector J. “On our best behaviour.” The 23rd International Joint Conference on Artificial Intelligence (IJCAI). August. 2013. pdf
• Rahman, Altaf, and Vincent Ng. “Resolving complex cases of definite pronouns: the winograd schema challenge.” Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning. Association for Computational Linguistics, 2012. pdf dataset dataset 2
• Roemmele, Melissa, Cosmin Adrian Bejan, and Andrew S. Gordon. “Choice of Plausible Alternatives: An Evaluation of Commonsense Causal Reasoning.” AAAI Spring Symposium: Logical Formalizations of Commonsense Reasoning. 2011. pdf dataset
• Levesque, Hector J., Ernest Davis, and Leora Morgenstern. “The Winograd schema challenge.” AAAI Spring Symposium: Logical Formalizations of Commonsense Reasoning. 2011. pdf
• Jerry R. Hobbs, Mark Stickel, Douglas Appelt, and Paul Martin. Interpretation as Abduction, Artificial Intelligence, 1993. pdf

Logical Inference

• Mohammad Shahed Sorower, Thomas G. Dietterich, Janardhan Rao Doppa Walker Orr, Prasad Tadepalli, and Xiaoli Fern. Inverting Grice’s Maxims to Learn Rules from Natural Language Extractions. NIPS 2011. pdf
• Ekaterina Ovchinnikova, Niloofar Montazeri, Theodore Alexandrov, Jerry R. Hobbs, Michael C. McCord and Rutu Mulkar-Mehta. Abductive Reasoning with a Large Knowledge Base for Discourse Processing. IWCS 2011. pdf
• James Blythe, Jerry R. Hobbs, Pedro Domingos, Rohit J. Kate and Raymond J. Mooney. Implementing Weighted Abduction in Markov Logic. IWCS2011. pdf
• Dan Garrette, Katrin Erk, Raymond Mooney. Integrating Logical Representations with Probabilistic Information using Markov Logic. IWCS2011. pdf
• Sindhu V. Raghavan, Raymond J. Mooney. Bayesian Abductive Logic Programs. AAAI 2010. pdf
• RohitJ. Kate RaymondJ. Mooney. Probabilistic Abduction using Markov Logic Networks. IJCAI 2009 on PAIR 2009. pdf
• Jerry R. Hobbs, Mark Stickel, Douglas Appelt, and Paul Martin. Interpretation as Abduction, Artificial Intelligence, 1993. pdf
• J. Bos (2009): Applying automated deduction to natural language understanding. Journal of Applied Logic 7(1): 100–112. pdf
• A Unified Approach to Abductive Inference (ARO 2008 MURI Project@University of Washington)

Discourse Theory

• Rhetorical Structure Theory
• Discourse Representation Theory
• J. Bos, M. Nissim (2008): Combining Discourse Representation Theory with FrameNet. In: R. Rossini Favretti (ed): Frames, Corpora, and Knowledge Representation, pp 169–183, Bononia University Press. pdf
• Dan Cristea, Nancy Ide and Laurent Romary. Veins Theory: A Model of Global Discourse Cohesion and Coherence. ACL 1998. pdf
• Barbara J. Grosz, Aravind K. Joshi and Scott Weinstein. Centering: A Framework for Modeling the Local Coherence of Discourse. Computational Linguistics, 1995. pdf
• Barbara J. Grosz and Candace L. Sidner. ATTENTION, INTENTIONS, AND THE STRUCTURE OF DISCOURSE. Computational Linguistics, 1986. pdf

• Bonnie Webber. Accounting for Discourse Relations: Constituency and Dependency. Intelligent Linguistic Architectures, 2006. pdf
• Florian Wolf, Edward Gibson. Representing Discourse Coherence: A Corpus-Based Study. Computational Linguistics, 2005.
• Bonnie Webber, Matthew Stone, Aravind Joshi and Alistair Knott. Anaphora and Discourse Structure. Computational Linguistics, 2003. pdf
• Daniel Marcu. A Formal and Computational Synthesis of Grosz and Sidner’s and Mann and Thompson’s theories. 1999. pdf
• Erhard Hinrichs. Discourse Annotation of Corpora. pdf
• Johanna D. Moore and Martha E. Pollack. A Problem for RST: The Need for Multi-Level Discourse Analysis. Computational Linguistics, 1992. pdf

Discourse Parsing

• Alexis Palmer, Afra Alishahi and Caroline Sporleder. Robust Semantic Analysis for Unseen Data in FrameNet. RANLP2011. pdf
• Michaela Regneri, Alexander Koller, Josef Ruppenhofer and Manfred Pinkal. Learning Script Participants from Unlabeled Data. RANLP2011. pdf
• Manfred Klenner and Don Tuggener. An Incremental Entity-Mention Model for Coreference Resolution with Restrictive Antecedent Accessibility. RANLP2011. pdf
• Ziheng Lin, Hwee Tou Ng and Min-Yen Kan. Automatically Evaluating Text Coherence Using Discourse Relation. ACL 2011. pdf

• Ziheng Lin, Hwee Tou Ng, and Min-Yen Kan. A PDTB-Styled End-to-End Discourse Parser. 2010. pdf

• Annie Louis, Rashmi Prasad, Aravind Joshi and Ani Nenkova. Using Entity Features to Classify Implicit Discourse Relations. SIGDIAL 2010. pdf
• Aria Haghighi and Dan Klein. Coreference Resolution in a Modular, Entity-Centered Model. NAACL-HLT 2010. pdf
• Emily Pitler, Annie Louis and Ani Nenkova. Automatic sense prediction for implicit discourse relations in text. ACL-IJCNLP 2009. pdf
• Rajen Subba and Barbara Di Eugenio. An effective Discourse Parser that uses Rich Linguistic Information. NAACL-HLT 2009. pdf
• Ravikiran Vadlapudi, Poornima Malepati and Suman Yelati. Hierarchical Discourse Parsing Based on Similarity Metrics. RANLP 2009. pdf
• Manfred Klenner, Étienne Ailloud. Optimization in Coreference Resolution is not Needed: A Nearly-Optimal Algorithm with Intensional Constraints. EACL 2009. pdf
• Jason Baldridge and Alex Lascarides. Probabilistic Head-Driven Parsing for Discourse Structure. CoNLL 2005. pdf
• Daniel Marcu and Abdessamad Echihabi. An Unsupervised Approach to Recognizing Discourse Relations. ACL 2002. pdf

Plan Recognition

• Parag Singla and Raymond J. Mooney. Abductive Markov Logic for Plan Recognition. AAAI2011. pp 1069-1075. pdf
• Nate Blaylock and James Allen. Hierarchical Instantiated Goal Recognition. MOO2006. pdf
• Nate Blaylock and James Allen. Fast Hierarchical Goal Schema Recognition. AAAI2006. pdf
• Douglas E. Appelt and Martha E. Pollack. Weighted Abduction for Plan Ascription. Technical Note 491, SRI International, 1992. pdf
• Sandra Carberry. Techniques for Plan Recognition. User Modeling and User-Adapted Interaction, 11(1-2), pp. 31-48, 2001. pdf

Corpus

• Penn Discourse Treebank
• RST Discourse Treebank
• Discourse Graphbank: paper LDC
• SDRT annotations of dialogues: DISCOR project

Knowledge Acquisition

• Doo Soon Kim and Bruce Poter. Integrating declarative knowledge : Issues, Algorithms and Future Work. AAAI2008. pdf
• Jonathan Berant, Tel Aviv and Jacob Goldberger. Global Learning of Typed Entailment Rules. ACL2011. (to appear) pdf
• Stefan Schoenmackers, Jesse Davis, Oren Etzioni and Daniel Weld. Learning First-Order Horn Clauses from Web Text. EMNLP2010. pdf
• Nathanael Chambers and Dan Jurafsky. Unsupervised Learning of Narrative Schemas and their Participants. ACL2010. pdf

Lectures

• University of Southern California: Introduction to NLP, Empirical Methods in Natural Language Processing
• MIT: Computational Models of Discourse
• Tohoku University: http://www.is.tohoku.ac.jp/_eng/introduction/laboratories/sis/iis_cs.html
• Story Understanding Resources
• David Poole and Alan Mackworth. Artificial Intelligence: Foundations of Computational Agents

Tools

• WOFMC
• Stanford CoreNLP
• Mini-TACITUS
• PRISM
• enju
• C&C tools

Misc.

• University of Texas at Austin Machine Learning Group: Publications
• Linguistic Problems and Complexities