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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 Mar. 4, 2020.

(We will continuously update this list.)


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

  4. Natural Language QA Approaches using Reasoning with External Knowledge. 2020. [paper]

    Authors: Chitta Baral, Pratyay Banerjee, Kuntal Pal, Arindam Mitra

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
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
Machine Reading Comprehension Using Structural Knowledge Graph-aware Network EMNLP
2019
short
ReCoRD paper
+ SG-Net: Syntax-Guided Machine Reading Comprehension AAAI
2020
SQuAD2.0
RACE
paper
+ Semantics-aware BERT for Language Understanding AAAI
2020
SQuAD2.0 paper
  • + indicates works regarding injecting knowledge to improve performance on the datasets not included in this summary.
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
CSQA 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
CSQA 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
Align, Mask and Select: A Simple Method for Incorporating Commonsense Knowledge into Language Representation Models 2019 CSQA
WSC
paper
Abductive Reasoning as Self-Supervision for Common Sense Question Answering 2019 Swag
HellaSwag
paper
Exploring ways to incorporate additional knowledge to improve Natural Language Commonsense Question Answering 2019 ANLI/
SocialIQA
paper
note
Graph-Based Reasoning over Heterogeneous External Knowledge for Commonsense Question Answering AAAI
2020
CSQA paper
note
K-ADAPTER: Infusing Knowledge into Pre-Trained Models with Adapters 2020 CosmosQA paper
note

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
Modeling Event Background for If-Then Commonsense Reasoning Using Context-aware Variational Autoencoder EMNLP
2019
Event2Mind paper
Dynamic Knowledge Graph Construction for Zero-shot Commonsense Question Answering 2019 SocialIQA
StoryCommonsense
paper
  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;
  3. [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;
  4. [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;
  5. [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;
  6. [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;
  7. 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;
  8. 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;
  9. [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;
  10. [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;
  11. 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;
  12. CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge. NAACL,2019. [paper / data]

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

    • Type: Multiple-Choice;
  13. ChID: A Large-scale Chinese IDiom Dataset for Cloze Test. ACL,2019. [paper / data]

    Authors: Chujie Zheng, Minlie Huang, Aixin Sun

    • Type: Cloze;
  14. [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;
  15. 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;
  16. SocialIQA: Commonsense Reasoning about Social Interactions. EMNLP,2019. [paper / data]

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

    • Type: Multiple-Choice;
  17. [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;
  18. 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;
  19. CODAH: An Adversarially-Authored Question Answering Dataset for Common Sense. ACL,2019,workshop. [paper / data ]

    Authors: Michael Chen, Mike D’Arcy, Alisa Liu, Jared Fernandez, Doug Downey

    • Type: Multiple-Choice;
  20. CommonGen: A Constrained Text Generation Dataset Towards Generative Commonsense Reasoning. 2019. [ paper / data ]

    Authors: Bill Yuchen Lin, Ming Shen, Yu Xing, Pei Zhou, Xiang Ren

    • Type: Generative;
  21. QASC: A Dataset for Question Answering via Sentence Composition. 2019. [paper / data ]

    Authors: Tushar Khot, Peter Clark, Michal Guerquin, Peter Jansen, Ashish Sabharwal

    • Type: Multiple-Choice;

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

Other Paper List About MRC

thunlp/RCPapers

PhD Thesis on MRC

  1. Neural Reading Comprehension and Beyond

    Author: Danqi Chen (Stanford University) Year: 2018

  2. 机器阅读理解的关键技术研究

    Author: Bingning Wang (Institute of Automation, Chinese Academy of Sciences) Year: 2018

  3. 机器阅读理解与文本问答技术研究

    Author: Minghao Hu (Graduate School of National University of Defense Technology) Year: 2019

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