Commonsense

Commonsense

Survey

Commonsense reasoning and commonsense knowledge in artificial intelligence

Ernest Davis, Gary Marcus
Dept. of Computer Science, New York University
Citation: 159

Types of Common-Sense Knowledge Needed for Recognizing Textual Entailment

Peter LoBue, Alexander Yates Temple University
ACL’11
Citation: 42

Dataset

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
University of Rochester
United States Naval Academy
Microsoft Research
Virginia Tech
The Institute for Human & Machine Cognition
HLT-NAACL’16
Citation: 128

ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning

Maarten Sap, Ronan Le Bras, Emily Allaway, Chandra Bhagavatula, Nicholas Lourie, Hannah Rashkin, Brendan Roof, Noah A. Smith, Yejin Choi
Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, USA
Allen Institute for Artificial Intelligence, Seattle, USA
AAAI’19
Citation: 29

  • ATOMIC focuses on inferential knowledge organized as typed If-Then relations. It has three types of If-Then knowledge, and nine new inferential dimensions. This knowledge graph contains 877k triples, 309K nodes, collected using 24K base events. The link for downloading the data is here.

ATOMIC

CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge

Alon Talmor, Jonathan Herzig, Nicholas Lourie, Jonathan Berant
School of Computer Science, Tel-Aviv University
Allen Institute for Artificial Intelligence
NAACL-HLT’19
Citation: 26

ConceptNet – A Practical Commonsense Reasoning Tool-kit

H Liu,P Singh
Citation: 1452

Event2Mind: Commonsense Inference on Events, Intents, and Reactions

Hannah Rashkin, Maarten Sap, Emily Allaway, Noah A. Smith, Yejin Choi
Paul G. Allen School of Computer Science & Engineering, University of Washington
Allen Institute for Artificial Intelligence
ACL’18
Citation: 22

ReCoRD: Bridging the Gap between Human and Machine Commonsense Reading Comprehension

Sheng Zhang, Xiaodong Liu, Jingjing Liu, Jianfeng Gao, Kevin Duh, Benjamin Van Durme
Johns Hopkins University
Microsoft Research
CoRR’18
Citation: 17

SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference

Rowan Zellers, Yonatan Bisk, Roy Schwartz, Yejin Choi
Paul G. Allen School of Computer Science & Engineering, University of Washington
Allen Institute for Artificial Intelligence
EMNLP’18
Citation: 77

The Winograd Schema Challenge

Hector J. Levesque, Ernest Davis, Leora Morgenstern
Dept. of Computer Science, University of Toronto
Dept. of Computer Science, New York University
S.A.I.C
KR’12
Citation: 298

Verb Physics: Relative Physical Knowledge of Actions and Objects

Maxwell Forbes, Yejin Choi
Paul G. Allen School of Computer Science & Engineering
University of Washington
ACL’17
Citation: 17

Analysis

Attention Is (not) All You Need for Commonsense Reasoning

Tassilo Klein, Moin Nabi
SAP Machine Learning Research, Berlin, Germany
ACL’19
Citation: 1

Cracking the Contextual Commonsense Code: Understanding Commonsense Reasoning Aptitude of Deep Contextual Representations

Jeff Da, Jungo Kasai
Paul G. Allen School of Computer Science & Engineering
University of Washington, Seattle, WA, USA
COIN@EMNLP’19
Citation: 0

Evaluating Commonsense in Pre-trained Language Models

Xuhui Zhou, Yue Zhang, Leyang Cui, Dandan Huang
University of Washington
School of Engineering, Westlake University
Zhejiang University
AAAI’20
Citation: 0

Language Models as Knowledge Bases?

Fabio Petroni, Tim Rocktaschelk, Patrick Lewis, Anton Bakhtin, Yuxiang Wu, Alexander H. Miller, Sebastian Riedel
Facebook AI Research
University College London
EMNLP’19
Citation: 9

Reporting bias and knowledge acquisition

Jonathan Gordon, Benjamin Van Durme
Dept of Computer Science, University of Rochester, Rochester, NY, USA
HLTCOE, Johns Hopkins University, Baltimore, MD, USA
AKBC@CIKM’13
Citation: 12

What do you learn from context? Probing for sentence structure in contextualized word representations

Ian Tenney, Patrick Xia, Berlin Chen, Alex Wang, Adam Poliak, R. Thomas McCoy, Najoung Kim, Benjamin Van Durme, Samuel R. Bowman, Dipanjan Das, Ellie Pavlick
Google AI Language
Johns Hopkins University
Swarthmore College
New York University
Brown University
ICLR’19
Citation: 51

What Does BERT Look at? An Analysis of BERT’s Attention

Kevin Clark, Urvashi Khandelwal, Omer Levy, Christopher D. Manning
Computer Science Department, Stanford University
Facebook AI Research
ACL’19
Citation: 25

Method

A Simple Method for Commonsense Reasoning

Trieu H. Trinh, Quoc V. Le
Google Brain
CoRR’18
Citation: 44

BIG MOOD: Relating Transformers to Explicit Commonsense Knowledge

Jeff Da
Paul G. Allen School of Computer Science & Engineering
University of Washington, Seattle, WA, USA
COIN@EMNLP’19
Citation: 0

COMET: Commonsense Transformers for Automatic Knowledge Graph Construction

Antoine Bosselut, Hannah Rashkin, Maarten Sap, Chaitanya Malaviya, Asli Celikyilmaz, Yejin Choi
Allen Institute for Artificial Intelligence, Seattle, WA, USA
Paul G. Allen School of Computer Science & Engineering, Seattle, WA, USA
Microsoft Research, Redmond, WA, USA
ACL’19
Citation: 3

Commonsense Knowledge Aware Conversation Generation with Graph Attention

Hao Zhou, Tom Young, Minlie Huang, Haizhou Zhao, Jingfang Xu, Xiaoyan Zhu
Conversational AI Group, AI Lab., Dept. of Computer Science, Tsinghua University
Beijing National Research Center for Information Science and Technology, China
School of Information and Electronics, Beijing Institute of Technology, China
Sogou Inc., Beijing, China
IJCAI’18
Citation: 51

Commonsense Knowledge Base Completion

Xiang Li, Aynaz Taheri, Lifu Tu, Kevin Gimpel
University of Chicago, Chicago
University of Illinois at Chicago, Chicago
Toyota Technological Institute at Chicago, Chicago
ACL’16
Citation: 36

Commonsense Knowledge Base Completion and Generation

Itsumi Saito, Kyosuke Nishida, Hisako Asano, Junji Tomita
NTT Media Intelligence Laboratories
CONLL’18
Citation: 7

Commonsense Knowledge Mining from Pretrained Models

Joshua Feldman, Joe Davison, Alexander M. Rush
School of Engineering and Applied Sciences, Harvard University
CoRR’19
Citation: 3

Explain Yourself! Leveraging Language Models for Commonsense Reasoning

Nazneen Fatema Rajani, Bryan McCann, Caiming Xiong, Richard Socher
Salesforce Research
ACL’19
Citaion: 8

Exploiting Structural and Semantic Context for Commonsense Knowledge Base Completion

Chaitanya Malaviya, Chandra Bhagavatula, Antoine Bosselut, Yejin Choi Allen Institute for Artificial Intelligence
University of Washington
CoRR’19
Citation: 1

Incorporating Context and External Knowledge for Pronoun Coreference Resolution

Hongming Zhang, Yan Song, Yangqiu Song
Department of CSE, The Hong Kong University of Science and Technology
Tencent AI Lab
NAACL-HLT’19
Citation: 3

KagNet: Knowledge-Aware Graph Networks for Commonsense Reasoning

Bill Yuchen Lin, Xinyue Chen, Jamin Chen, Xiang Ren
Computer Science Department, University of Southern California
Computer Science Department, Shanghai Jiao Tong University
EMNLP-IJCNLP’19
Citation: 4

Knowledge-aware Pronoun Coreference Resolution

Hongming Zhang, Yan Song, Yangqiu Song, Dong Yu
Department of CSE, The Hong Kong University of Science and Technology
Tencent AI Lab
ACL’19
Citation: 1

Reasoning With Neural Tensor Networks for Knowledge Base Completion

Richard Socher, Danqi Chen, Christopher D. Manning, Andrew Y. Ng
Computer Science Department, Stanford University, Stanford
NIPS’13
Citation: 1032

Story Ending Generation with Incremental Encoding and Commonsense Knowledge

Jian Guan, Yansen Wang, Minlie Huang
Dept. of Computer Science & Technology, Tsinghua University
Institute for Artificial IntelligenceTsinghua University (THUAI)
Beijing National Research Center for Information Science and Technology
Dept. of Physics, Tsinghua University
AAAI’19
Citation: 13