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

前期: Wednesday 16:20-17:50 後期: Wednesday 13:00-14:40

Member

乾, 岡﨑, 井之上, 磯部, Paul, 稲田, 小林, 横井, 高橋, 佐藤, 清野, 赤間

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

後期の方針 †

• 方針
  • paper reading only
  • （進捗報告は KIAI で）
• 読む人
  • 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
• 聞く人
  • 各回1度は質問・コメントをする

Schedule †

Future †

Upcoming †

Done †

後期 †

• 2/24 (Fri) 10:30
  • 参加者: 乾 (Skype), 磯部, Paul, 横井, 高橋, 赤間
  • 横井
    • Matt Kusner, Yu Sun, Nicholas Kolkin, and Kilian Weinberger. “From Word Embeddings To Document Distances.” ICML, 2015.
    • paper, 🔒paper(annotated)
  • 高橋
    • Kolesnyk, Vladyslav, Tim Rocktäschel, and Sebastian Riedel. "Generating Natural Language Inference Chains." arXiv preprint arXiv:1606.01404 (2016).
    • paper, 🔒memo

• 2/15 (Wed) 13:30
  • 参加者: 磯部, Paul, 稲田, 横井, 清野, 赤間, 鈴木
  • Paul
    • Computational Argumentation Quality Assessment in Natural Language; Wachsmuth et al., EACL 2017 (to appear)
    • paper 🔒Annotated Paper
  • 赤間
    • A Neural Network Approach for Knowledge-Driven Response Generation;Pavlos Vougiouklis, Jonathon Hare, Elena Simperl, COLING 2016
    • paper slide

• 2/8 (Wed) 13:00
  • 清野
    • 文対モデリングの話 🔒内部資料
    • An Empirical Evaluation of various Deep Learning Architectures for Bi-Sequence Classification Tasks (COLING 2016) Paper
    • Modelling Interaction of Sentence Pair with Coupled-LSTMs (EMNLP 2016) Paper
    • A Decomposable Attention Model for Natural Language Inference (EMNLP 2016) Paper

• 2/1 (Wed) 13:00 中止

• 1/11 (Wed) 13:00
  • Paul
    • What’s in an Explanation? Characterizing Knowledge and Inference Requirements for Elementary Science Exams, COLING2016
    • Paper
    • 🔒Annotated Paper
  • 赤間
    • An annotated corpus of film dialogue for learning and characterizing character style.; Marilyn A. Walker+, LREC 2012
    • paper paper(learning) 🔒paper(generating) 🔒slide

• (12/14 COLING のためおやすみ)

• 12/07 (Wed) 13:00
  • 参加者: 乾, 松田, 磯部, Paul, 稲田, 横井, 佐藤, 鈴木, 清野, 赤間, 塙
  • 横井
    • Zhongyuan Wang, Haixun Wang, Ji-Rong Wen, and Yanghua Xiao. “An Inference Approach to Basic Level of Categorization.” CIKM, 2015.
    • Paper, 🔒Paper (annotated), 🔒Memo
    • 参考: Microsoft Concept Graph (Probase), Demo, Understanding Short Text (ACL 2016 Tutorial)

• 11/30 (Wed) 13:00
  • 稲田
    • Improving Hypernymy Detection with an Integrated Path-based and Distributional Method, ACL2016
    • paper, 🔒内部資料

• 11/22 (Tue) 11:00
  • 参加者: 乾, 岡﨑, 磯部, Paul, 横井, 高橋, 佐藤, 清野, 赤間, 佐々翔, 塙
  • 清野
    • One Vector is Not Enough: Entity-Augmented Distributed Semantics for Discourse Relations; Yangfeng Ji and Jacob Eisenstein, TACL 2015
    • 🔒Slide 🔒Paper (annotated) Paper
    • 🔒岡崎さん資料(適宜使います)
  • 赤間
    • A Diversity-Promoting Objective Function for Neural Conversation Models; Jiwei Li+, NAACL 2016
    • paper 🔒slide

• 11/9 (Wed) 13:00
  • 参加者: 水本, 磯部, Paul, 横井, 高橋, 佐藤, 清野, 赤間
  • 佐藤
    • "How NOT To Evaluate Your Dialogue System: An Emprical Study of Unsupervised Evaluation Metrics for Dialogue Response Generation", Chia-Wei Liu , Ryan Lowe , Iulian V. Serban, Michael Noseworthy, Laurent Charlin, Joelle Pineau, EMNLP 2016
    • paper
    • annotated paper: 🔒内部資料
    • 参考文献: Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models

• 11/2 (Wed) 13:00
  • 参加者: 磯部, Paul, 稲田, 横井, 高橋, 清野, 赤間, 塙
  • Paul
    • Reed et al. "NLP Approaches to Computational Argumentation" ACL 2016 Tutorial(ACL): 🔒Slides
  • 高橋
    • Chen, Jifan, et al. "Implicit discourse relation detection via a deep architecture with gated relevance network." Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL). 2016.
    • paper 🔒paper(annotated)

• 10/26 (Wed) 13:00
  • 参加者: 乾, 磯部, 稲田, 横井, 高橋, 佐藤, 清野, 赤間, 佐々翔, 塙
  • 稲田
    • A Persona-Based Neural Conversation Model; Jiwei Li, Michel Galley, Chris Brockett, Georgios P. Spithourakis, Jianfeng Gao, Bill Dolan; ACL 2016
    • paper 🔒内部資料

• 10/18 (Tue) 14:40
  • 参加者: 岡﨑, Paul, 高瀬, 横井, 高橋, 佐藤, 清野, 赤間, 佐々翔
  • Paper Reading (清野)
    • Mostafazadeh, Nasrin, et al. "Generating Natural Questions About an Image." ACL 2016
    • paper・Supplementary Material・🔒スライド

• 10/12 (Wed) 13:00
  • 参加者: Paul, 稲田, 横井, 高橋, 佐藤, 鶴田, 清野, 赤間, 佐々翔, 塙
  • 横井
    • Tatsunori Hashimoto, David Alvarez-Melis, and Tommi Jaakkola. “Word Embeddings as Metric Recovery in Semantic Spaces,” Transactions of the Association of Computational Linguistics (TACL), 4 (2016), pp.273--286. ACL Anthology, slide
  • 佐藤
    • Sungjin Ahn, Heeyoul Choi, Tanel Pärnamaa, and Yoshua Bengio, "A Neural Knowledge Language Model", arxiv, paper, 🔒内部資料

• 9/28 (Wed) 14:30
  • 参加者: 乾, Paul, 横井, 高橋, 佐藤, 清野, 赤間, 佐々翔 (w/代勤, 島岡)
  • 今後の方針決め

前期 †

• 7/13 (Wed) 16:20
  • Progress Report (佐藤) 🔒内部資料

• 7/6 (Wed) 16:20
  • Paper Reading (横井)
    • Manaal Faruqui, Ryan Mcdonald, and Radu Soricut, “Morpho-Syntactic Lexicon Generation Using Graph-Based Semi-Supervised Learning”, Transactions of the Association of Computational Linguistics (TACL), 4 (2016), 1–16. ACL Anthology, 🔒paper(annotated)

• 6/22 (Wed) 16:20
  • Progress Report (Paul) 🔒内部資料
  • Paper Reading (井之上)
    • William W. Cohen. TensorLog: A Differentiable Deductive Database. (🔒内部資料)
    • paper, NAACL tutorial, slides

• 6/15 (Wed) 16:40
  • Paper Reading (高橋)
    • J. Nilsson, J. Fredriksson, and E. Coelingh, “Rule-Based Highway Maneuver Intention Recognition,” in 2015 IEEE 18th International Conference on Intelligent Transportation Systems, 2015, pp. 950–955.
    • paper (original), 🔒paper (anotated)

• 6/8 (Wed) 16:20
  • Paper Reading (横井)
    • Vladyslav Kolesnyk, Tim Rocktäschel, Sebastian Riedel. Generating Natural Language Inference Chains. arXiv (EMNLP 2016 short, under reviewing?)

• 5/25 (Wed) 17:00 (総合研究会終了後)
  • Paper Reading (高橋)
    • Mariusz Bojarski, Davide Del Testa, Daniel Dworakowski, Bernhard Firner, Beat Flepp, Prasoon Goyal, Lawrence D. Jackel, Mathew Monfort, Urs Muller, Jiakai Zhang, Xin Zhang, Jake Zhao, Karol Zieba, “End to End Learning for Self-Driving Cars,” arXiv, 2016 paper
  • Paper Reading (小林)
    • 画像界隈に関するサーベイ雑談

• 5/18 (Wed) 16:20
  • Paper Reading (小林)
    • Feuding Families and Former Friends; Unsupervised Learning for Dynamic, Fictional Relationships. Mohit Iyyer, Anupam Guha, Snigdha Chaturvedi, Jordan Boyd-Graber and Hal Daumé III, NAACL 2016 Best paper
    • Learning to Compose Neural Networks for Question Answering. Jacob Andreas, Marcus Rohrbach, Trevor Darrell and Dan Klein, NAACL 2016 Best paper
  • Progress Report (Paul)
    • Towards understanding Argumentation Logic via Causality 🔒内部資料

• 5/10 (Tue) 8:50
  • Progress Report (井之上)
    • 🔒内部資料
  • Paper Reading (横井)
    • Shindo+. Bayesian Symbol-Refined Tree Substitution Grammars for Syntactic Parsing. ACL 2012. (Best Paper Award) paper, slide, 日本語paper, 日本語slide
    • (準備)木置換文法の学習：進藤. 統計的手法による文法モデリングと構文解析. 2012. slide
    • (準備)ノンパラメトリックベイズ：持橋. Nonparametric Bayes for Non-Bayesians. 2008. slide

• 4/28 (Thu) 8:50
  • Paper Reading (小林)
    • A Corpus and Cloze Evaluation for Deeper Understanding of Commonsense Stories. Nasrin Mostafazadeh, Nathanael Chambers, Xiaodong He, Devi Parikh, Dhruv Batra, Lucy Vanderwende, Pushmeet Kohli, James Allen, NAACL 2016 (to appear)
    • 🔒paper (annotated), paper (original)
  • Paper Reading (佐藤)
    • Learning Natural Language Inference with LSTM, Shuohang Wang, Jing Jiang, NAACL 2016(to appear)
    • paper(arXiv), 🔒内部資料
    • 参考: A large annotated corpus for learning natural language inference, Samuel R. Bowman,　Gabor Angeli, Christopher Potts, and Christopher D. Manning, EMNLP 2015
    • 参考: Long Short-Term Memory-Networks for Machine Reading, Jianpeng Cheng, Li Dong, Mirella Lapata, arXiv

• 4/20 (Wed) 16:20
  • Progress Report (Paul) 🔒内部資料
  • Progress Report (高橋)
    • Traffic Risk Prediction Based on Traffic Ontology and Explanation Generation 🔒内部資料

• 4/14 (Thu) 8:50 Kick-off Meeting
  • 井之上: 🔒内部資料
  • メンバーによる研究紹介
    • 井之上: 🔒内部資料
    • Paul: 🔒内部資料
    • 小林: 🔒内部資料
    • 高橋: 🔒内部資料

Assignment †

後期 †

前期 †

Past †

• 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