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All Projects → IndexFziQ → KMRC-Papers

IndexFziQ / KMRC-Papers

Licence: MIT license
A list of recent papers regarding knowledge-based machine reading comprehension.

Labels

nlpknowledgepaperknowledge-basereading-comprehensionmachine-reading-comprehension

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Papers on Knowledge-based Machine Reading Comprehension.

A list of recent papers about Knowledge-based Machine Reading Comprehension (KMRC).

Contributed by Luxi Xing and Yuqiang Xie.

Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China.

Update on Oct. 23, 2019.

(the current version only contains the works published on the conferences or journals, we will continuously update this list.)

Because of some mistakes, this version can not be updated. For the latest version, please jump to KMRC-Research-Archive.

Content

  1. Survey
  2. Cloze Style Tasks
  3. Span Extraction Tasks
  4. Multiple Choice Tasks
  5. Generation Tasks
  6. Datasets

Survey Papers

  1. Commonsense Reasoning for Natural Language Understanding: A Survey of Benchmarks, Resources, and Approaches. 2019. [paper / note]

    Authors: Shane Storks, Qianzi Gao, Joyce Y. Chai

  2. Neural Machine Reading Comprehension: Methods and Trends. 2019. [paper]

    Authors: Shanshan Liu, Xin Zhang, Sheng Zhang, Hui Wang, Weiming Zhang

  3. Machine Reading Comprehension: a Literature Review. 2019. [paper]

    Authors: Xin Zhang, An Yang, Sujian Li, Yizhong Wang

Cloze Style Tasks

Title Publish Tasks Links
Reasoning with Heterogeneous Knowledge for Commonsense Machine Comprehension ACL
2017		 SCT paper
World Knowledge for Reading Comprehension: Rare Entity Prediction with Hierarchical LSTMs Using External Descriptions EMNLP
2017		 Rare Entity Prediction paper
Knowledgeable Reader: Enhancing Cloze-Style Reading Comprehension with External Commonsense Knowledge ACL
2018		 Common Nouns paper
note
A Multi-Attention based Neural Network with External Knowledge for Story Ending Predicting Task COLING
2018		 SCT paper
Incorporating Structured Commonsense Knowledge in Story Completion AAAI
2018		 SCT paper
Story Ending Prediction by Transferable BERT IJCAI
2019		 SCT paper

Span Extraction Tasks

Title Publish Tasks Links
Dynamic Integration of Background Knowledge in Neural NLU Systems 2018 SQuAD/
TriviaQA		 paper
note
Explicit Utilization of General Knowledge in Machine Reading Comprehension ACL
2019		 SQuAD paper
note
Enhancing Pre-Trained Language Representations with Rich Knowledge for Machine Reading Comprehension ACL
2019		 SQuAD/
ReCoRD		 paper
note

Multiple Choice Tasks

Title Publish Tasks Links
Yuanfudao at SemEval-2018 Task 11: Three-way Attention and Relational Knowledge for Commonsense Machine Comprehension SemEval
2018		 SemEval-2018 Task 11 paper
code
Improving Question Answering by Commonsense-Based Pre-Training AAAI
2019		 ARC/
OpenBookQA/
SemEval-2018 Task 11		 paper
Improving Machine Reading Comprehension with General Reading Strategies NAACL
2019		 ARC/ OpenBookQA/ MCTest/
SemEval-2018 Task 11/ SCT/ MultiRC		 paper
code
Ranking and Selecting Multi-Hop Knowledge Paths to Better Predict Human Needs NAACL
2019		 story commonsense paper
code
Incorporating Relation Knowledge into Commonsense Reading Comprehension with Multi-task Learning CIKM
2019		 SemEval-2018 Task 11 / SCT paper
Explain Yourself! Leveraging Language Models for Commonsense Reasoning ACL
2019		 CommonsenseQA paper
code
note
Careful Selection of Knowledge to solve Open Book Question Answering ACL
2019		 OpenBookQA paper
Improving Question Answering with External Knowledge EMNLP
MRQA
2019		 ARC/
OpenBookQA		 paper
note
KagNet: Knowledge-Aware Graph Networks for Commonsense Reasoning EMNLP
2019		 CommonsenseQA paper
code
note
What’s Missing: A Knowledge Gap Guided Approach for Multi-hop Question Answering EMNLP
2019		 OpenBookQA paper
note
BIG MOOD: Relating Transformers to Explicit Commonsense Knowledge EMNLP
COIN
2019		 MCScripts v2 paper

Generation Tasks

Also known as Free-form Answer Tasks

Title Publish Tasks Links
Commonsense for Generative Multi-Hop Question Answering Tasks EMNLP
2018		 NarrativeQA/
WikiHop		 paper
code
note
COMET: Commonsense Transformers for Automatic Knowledge Graph Construction ACL
2019		 Atomic paper
code
note
Incorporating External Knowledge into Machine Reading for Generative Question Answering EMNLP
2019		 MS MARCO paper
note

Benchmark Datasets

  1. [COPA] Choice of Plausible Alternatives: An Evaluation of Commonsense Causal Reasoning. AAAI,2011. [paper / data]

    Authors: Melissa Roemmele, Cosmin Adrian Bejan, Andrew S. Gordon

    • Type: Multiple-Choice;

  2. [WSC] The Winograd Schema Challenge. AAAI,2011. [paper /data]

    Authors: Hector J. Levesque, Ernest Davis, Leora Morgenstern

  • Type: Multiple-Choice;

  1. [ROCStories; SCT] A Corpus and Cloze Evaluation for Deeper Understanding of Commonsense Stories. NAACL,2016. [paper / data]

    Authors: Nasrin Mostafazadeh, Nathanael Chambers, Xiaodong He, Devi Parikh, Dhruv Batra, Lucy Vanderwende, Pushmeet Kohli, James Allen

    • Type: Cloze;

  2. [NarrativeQA] The NarrativeQA Reading Comprehension Challenge. TACL,2018. [paper / data]

    Authors: Tomáš Kočiský, Jonathan Schwarz, Phil Blunsom, Chris Dyer, Karl Moritz Hermann, Gábor Melis, Edward Grefenstette

    • Type: Generation;

  3. [SemEval-2018 Task 11] MCScript: A Novel Dataset for Assessing Machine Comprehension Using Script Knowledge. LERC,2018. [paper / data]

    Authors: Simon Ostermann, Ashutosh Modi, Michael Roth, Stefan Thater, Manfred Pinkal

    • Type: Multiple-Choice;

  4. [story-commonsense] Modeling Naive Psychology of Characters in Simple Commonsense Stories. ACL,2018. [paper / data]

    Authors: Hannah Rashkin, Antoine Bosselut, Maarten Sap, Kevin Knight, Yejin Choi

    • Type: Multiple-Choice;

  5. Event2Mind: Commonsense Inference on Events, Intents, and Reactions. ACL,2018. [paper / data]

    Authors: Hannah Rashkin, Maarten Sap, Emily Allaway, Noah A. Smith, Yejin Choi

    • Types: Generation;

  6. ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning. AAAI,2019. [paper / data]

    Authors: Maarten Sap, Ronan LeBras, Emily Allaway, Chandra Bhagavatula, Nicholas Lourie, Hannah Rashkin, Brendan Roof, Noah A. Smith, Yejin Choi

    • Types: Generation;

  7. [ARC] Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge. 2018. [paper / data]

    Authors: Peter Clark, Isaac Cowhey, Oren Etzioni, Tushar Khot, Ashish Sabharwal, Carissa Schoenick, Oyvind Tafjord

    • Type: Multiple-Choice;

  8. [OpenBookQA] Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering. EMNLP,2018. [paper / data]

    Authors: Todor Mihaylov, Peter Clark, Tushar Khot, Ashish Sabharwal

    • Type: Multiple-Choice;

  9. ReCoRD: Bridging the Gap between Human and Machine Commonsense Reading Comprehension. 2018. [paper / data]

    Authors: Sheng Zhang, Xiaodong Liu, Jingjing Liu, Jianfeng Gao, Kevin Duh, Benjamin Van Durme

    • Type: Cloze;

  10. CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge. NAACL,2019. [paper / data]

    Authors: Alon Talmor, Jonathan Herzig, Nicholas Lourie, Jonathan Berant

    • Type: Multiple-Choice;

  11. ChID: A Large-scale Chinese IDiom Dataset for Cloze Test. ACL,2019. [paper / data]

    Authors: Chujie Zheng, Minlie Huang, Aixin Sun

    • Type: Cloze;

  12. [sense-making] Does it Make Sense? And Why? A Pilot Study for Sense Making and Explanation. ACL,2019. [paper / data]

    Authors: Cunxiang Wang, Shuailong Liang, Yue Zhang, Xiaonan Li, Tian Gao

    • Type: Multiple-Choice;

  13. HellaSwag: Can a Machine Really Finish Your Sentence? ACL,2019. [paper / data]

    Authors: Rowan Zellers, Ari Holtzman, Yonatan Bisk, Ali Farhadi, Yejin Choi

    • Type: Multiple-Choice;

  14. SocialIQA: Commonsense Reasoning about Social Interactions. EMNLP,2019. [paper / data]

    Authors: Maarten Sap, Hannah Rashkin, Derek Chen, Ronan LeBras, Yejin Choi

    • Type: Multiple-Choice;

  15. [ANLI] Abductive Commonsense Reasoning. 2019. [paper / data]

    Authors: Chandra Bhagavatula, Ronan Le Bras, Chaitanya Malaviya, Keisuke Sakaguchi, Ari Holtzman, Hannah Rashkin, Doug Downey, Scott Wen-tau Yih, Yejin Choi

    • Type: Multiple-Choice;

  16. Cosmos QA: Machine Reading Comprehension with Contextual Commonsense Reasoning. EMNLP,2019. [paper / data]

    Authors: Lifu Huang, Ronan Le Bras, Chandra Bhagavatula, Yejin Choi

    • Type: Multiple-Choice;

Note: Only consider the benchmark datasets/tasks which require knowledge to complete.

Other Paper List About MRC

thunlp/RCPapers

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