FrontPage / SIG Discourse

Special Interest Group on Discourse (SIG Discourse) discusses research progress of our member (5-10 min. each) and interesting findings of past/state-of-the-art researches (30 min.). The schedule is listed below.


  • 1st Semester: Wed 13:00-14:30


乾, 井之上, Paul, 横井, 高橋, 清野, 赤間, 白井, 栗林, 大内, 佐藤(志), 大竹, Ana

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



  • 多読会
    • 目的
      • 最新論文100本を多読し、分野の方向感掴み、脳内へのポインタ作りを行う
      • 多読力をつける (短い時間で研究の概形を把握する, 短い時間で疑問/感想を持つ)
    • 実施要領
      • 3本 x {7, 8, 9,10}人 (コアメン) = 最低20本程度の論文を多読する
      • 1本3分でやる
      • 目標: 100本
      • 詳しくは🔒こちら
  • 個別議論
    • 各回3名が担当
      • 論文紹介・研究進捗報告など、自由に選んでよい
      • 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
    • 精読
      • 発表前に読む論文を #random で紹介
      • 30分でQA含めキッチリ切る。
    • 進捗
      • 30-40分でQA含め。普段の総合研究会より深めの議論をするため。
      • 進捗は議論が長くなる傾向にあるので、進捗が少なくとも一個入るならば2セットで勉強会を組む
  • 聞きかた
    • 各回1度は質問・コメントをする



  • Thu 3/7 10:30-
    • 精読 or 進捗:
    • 精読 or 進捗:
    • 精読 or 進捗:
  • Thu 2/28 10:30-
    • 精読: 赤間 (2)
    • 精読 or 進捗: 大内 (3)
    • 精読 or 進捗: 高橋 (3)
  • Thu 2/14 10:30-
  • 精読: 清野 (2)
  • 精読: 白井 (3) What Is One Grain of Sand in the Desert ? Analyzing Individual Neurons in Deep NLP Models, AAAI2019.


  • Thu 1/31 10:30-
    • 進捗: 大竹 (2)
      • 顕現的要素の出現順序に基づく物語の類似性尺度 🔒内部資料
    • 精読 or 進捗: 栗林 (2)
    • 精読 or 進捗: 内藤 (2)
  • Thu 12/13 10:30-
    • 精読: 横井 (2)
      • McInnes+'18, UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction, arXiv
      • paper, 🔒内部資料
    • 精読: 高橋 (2)
      • Yuhao Zhang, Peng Qi, Christopher D. Manning. Graph Convolution over Pruned Dependency Trees Improves Relation Extraction. EMNLP 2018
      • paper, 🔒内部資料
  • Thu 12/6 10:30-
    • 精読: 佐藤 (志)
      • Yang Zhao, Yining Wang, Jiajun Zhang, Chengqing Zong. Phrase Table as Recommendation Memory for Neural Machine Translation. IJCAI 2018
      • paper 🔒内部資料
    • 進捗: 大内 (2)
    • 精読: 赤間 (1)
      • Lajanugen Logeswaran, Honglak Lee, Samy Bengio. Content preserving text generation with attribute controls. NIPS2018
      • paper, 内部資料
  • Thu 11/29 10:30-
    • 精読1: 井之上 (1)
      • Haitian Sun, Bhuwan Dhingra, Manzil Zaheer, Kathryn Mazaitis, Ruslan Salakhutdinov, William W. Cohen. Open Domain Question Answering Using Early Fusion of Knowledge Bases and Text. EMNLP 2018.
      • paper 🔒内部資料
    • 精読2: 大竹
      • Towards Automatically Extracting Story Graphs from Natural Language Stories (Josep Valls-Vargas, et al., AAAI2017 Workshop on What's Next for AI in Games?)
      • paper 🔒内部資料
    • 進捗: 白井 (1) 🔒内部資料
  • Thu 11/22 10:30-
    • 多読会5 (92本目〜108本目 🎉) 🔒資料
  • Thu 11/15 10:30
    • 多読会4 (67本目〜) 🔒資料
  • Thu 10/25 10:30-
    • 精読1: 井之上
      • Haitian Sun, Bhuwan Dhingra, Manzil Zaheer, Kathryn Mazaitis, Ruslan Salakhutdinov, William W. Cohen. Open Domain Question Answering Using Early Fusion of Knowledge Bases and Text. EMNLP 2018.
      • paper 内部資料
    • 精読2: 栗林
      • Jiaqi Mu, Pramod Viswanath. All-but-the-Top: Simple and Effective Postprocessing for Word Representations. ICLR 2018.
      • Mikhail Khodak, Nikunj Saunshi, Yingyu Liang, Tengyu Ma, Brandon Stewart, Sanjeev Arora. A La Carte Embedding: Cheap but Effective Induction of Semantic Feature Vectors. ACL2018.
      • All-but-the-Top A La Carte 🔒内部資料
    • 進捗: 内藤 🔒進捗報告
  • Thu 10/18 10:30-
    • 精読1: 横井
      • David Alvarez-Melis, Tommi S. Jaakkola. Gromov-Wasserstein Alignment of Word Embedding Spaces. EMNLP 2018.
      • arXiv, 🔒内部資料
    • 精読2: 高橋
      • Eunsol Choi, He He, Mohit Iyyer, Mark Yatskar, Wen-tau Yih, Yejin Choi, Percy Liang, Luke Zettlemoyer. QuAC : Question Answering in Context. EMNLP 2018.
      • paper, 🔒annotated paper
    • 進捗: 佐藤S 🔒進捗報告
  • Thu 10/11 10:30-
    • 多読会3 (42本目〜) 🔒資料
  • Fri 10/5 14:15-
    • 多読会2 (23本目〜) 🔒資料
  • Wed 9/26 13:00-
    • 続・なつやすみの... (B4)
    • 多読会1 (1本目〜) 🔒資料
  • Wed 9/19 13:00-
    • なつやすみの...
  • Wed 7/25 13:00-
    • B team
    • 井之上 🔒内部資料
      • Hannah Rashkin, Maarten Sap, Emily Allaway, Noah A. Smith, and Yejin Choi. Event2Mind: Commonsense Inference on Events, Intents, and Reactions. ACL2018. paper project home
  • Wed 7/11 13:00-
    • A team
    • 内藤
  • Wed 7/4 13:00-
    • B team
    • 赤間 ごめんなさい
  • Wed 6/20 13:00-
    • B team
    • 白井 🔒esa
  • Wed 4/25 13:00-
    • A team


  • v: presented
  • (v): assigned



A横井, 清野, 白井, 大内, 佐藤(志)
B井之上, 高橋, 赤間, 栗林



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


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




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