/Reading-Comprehension-Question-Answering-Papers

Survey on Machine Reading Comprehension

New Papers from EMNLP 2019 about MRC

  • Minghao Hu, Yuxing Peng, Zhen Huang and Dongsheng Li, A Multi-Type Multi-Span Network for Reading Comprehension that Requires Discrete Reasoning, link.
  • Huazheng Wang, Zhe Gan, Xiaodong Liu, Jingjing Liu, Jianfeng Gao and Hongning Wang, Adversarial Domain Adaptation for Machine Reading Comprehension, link?.
  • Yimin Jing, Deyi Xiong and Zhen Yan, BiPaR: A Bilingual Parallel Dataset for Multilingual and Cross-lingual Reading Comprehension on Novels, link?.
  • Lifu Huang, Ronan Le Bras, Chandra Bhagavatula and Yejin Choi, Cosmos QA: Machine Reading Comprehension with Contextual Commonsense Reasoning, link?.
  • Yiming Cui, Wanxiang Che, Ting Liu, Bing Qin, Shijin Wang and Guoping Hu, Cross-Lingual Machine Reading Comprehension, link?.
  • Todor Mihaylov and Anette Frank, Discourse-Aware Semantic Self-Attention for Narrative Reading Comprehension, link?.
  • Kyungjae Lee, Sunghyun Park, Hojae Han, Jinyoung Yeo, Seung-won Hwang and Juho Lee, Learning with Limited Data for Multilingual Reading Comprehension, link?.
  • Qiu Ran, Yankai Lin, Peng Li, Jie Zhou and Zhiyuan Liu, NumNet: Machine Reading Comprehension with Numerical Reasoning, link?.
  • Yiming Cui, Ting Liu, Wanxiang Che, Li Xiao, Zhipeng Chen, Wentao Ma, Shijin Wang and Guoping Hu, A Span-Extraction Dataset for Chinese Machine Reading Comprehension, link?.
  • Daniel Andor, Luheng He, Kenton Lee and Emily Pitler, Giving BERT a Calculator: Finding Operations and Arguments with Reading Comprehension, link?.
  • Delai Qiu, Yuanzhe Zhang, Xinwei Feng, Xiangwen Liao, Wenbin Jiang, Yajuan Lyu, Kang Liu and Jun Zhao, Machine Reading Comprehension Using Structural Knowledge Graph-aware Network, link?.
  • Pradeep Dasigi, Nelson F. Liu, Ana Marasovic, Noah A. Smith and Matt Gardner, Quoref: A Reading Comprehension Dataset with Questions Requiring Coreferential Reasoning, link?.
  • Tsung-Yuan Hsu, Chi-Liang Liu and Hung-yi Lee, Zero-shot Reading Comprehension by Cross-lingual Transfer Learning with Multi-lingual Language Representation Model, link?.

New Papers from ACL 2019 about MRC

  • Yimeng Zhuang and Huadong Wang, Token-level Dynamic Self-Attention Network for Multi-Passage Reading Comprehension, link.
  • Chao Wang and Hui Jiang, Explicit Utilization of General Knowledge in Machine Reading Comprehension, link.
  • Kyosuke Nishida et al., Multi-style Generative Reading Comprehension, link.
  • Minghao Hu, Yuxing Peng, Zhen Huang and Dongsheng Li, Retrieve, Read, Rerank: Towards End-to-End Multi-Document Reading Comprehension, link.
  • Ming Ding et al., Cognitive Graph for Multi-Hop Reading Comprehension at Scale, link.
  • Ming Tu et al., Multi-hop reading comprehension across multiple documents by reasoning over heterogeneous graphs, link.
  • An Yang et al., Enhancing Pre-Trained Language Representations with Rich Knowledge for Machine Reading Comprehension, link.
  • Alon Talmor and Jonathan Berant, MultiQA: An Empirical Investigation of Generalization and Transfer in Reading Comprehension, link.
  • Yichen Jiang el at., Explore, Propose, and Assemble: An Interpretable Model for Multi-Hop Reading Comprehension, link.
  • Yi Tay et al., Simple and Effective Curriculum Pointer-Generator Networks for Reading Comprehension over Long Narratives, link.
  • Sewon Min et al., Multi-hop Reading Comprehension through Question Decomposition and Rescoring, link.
  • Souvik Kundu et al., Exploiting Explicit Paths for Multi-hop Reading Comprehension, link.
  • Haichao Zhu et al., Learning to Ask Unanswerable Questions for Machine Reading Comprehension, link.
  • Xuanyu Zhang, MC^2: Multi-perspective Convolutional Cube for Conversational Machine Reading Comprehension, link.
  • Diana Galvan, Active Reading Comprehension: A dataset for learning the Question-Answer Relationship strategy, link.

Survey/Overview papers/documents should read on Machine Reading Comprehension

  • Danqi Chen: Neural Reading Comprehension and Beyond. PhD thesis, Stanford University, 2018, link.
  • Boyu Qiu et al., A Survey on Neural Machine Reading Comprehension, arXiv, 2019, link.
  • Xin Zhang et al., Machine Reading Comprehension: a Literature Review, arXiv, 2019, link.
  • Shanshan Liu et al., Neural Machine Reading Comprehension: Methods and Trends, arXiv, 2019, link.

Papers/Models

Noted

  • KBMRC: Knowledge-based Machine Reading Comprehension
  • OPQA: Open-domain Question Answering
Year Title Model Conference Author/Team Datasets Misc Paper, Source Code
2015 Teaching Machines to Read and Comprehend NIPS Google DeepMind, University of Oxford CNN and Daily Mail paper, code
2016 Text Understanding with the Attention Sum Reader Network ACL IBM Watson Children’s Book Test, CNN and Daily Mail paper, code
2016 Key-Value Memory Networks for Directly Reading Documents EMNLP Facebook AI Research, CMU WikiMovies, WikiQA KBMRC paper, code
2017 Bi-directional Attention Flow for Machine Comprehension BiDAF ICLR University of Washington, Allen Institute SQuAD 1.1 paper, code
2017 Machine Comprehension Using Match-LSTM and Answer Pointer ICLR Singapore Management University SQuAD 1.1 paper, code
2017 R-Net: Machine Reading Comprehension with Self-Matching Networks R-Net Technical Report Microsoft Research Asia SQuAD 1.1, MS-MARCO paper, code
2017 Reading Wikipedia to Answer Open-Domain Questions DrQA ACL Danqi Chen et al., SQuAD 1.1, CuratedTREC, WebQuestions, WikiMovies OPQA paper, code
2017 Gated-Attention Readers for Text Comprehension ACL CMU CNN and Daily Mail, Children’s Book Test, Who Did What paper, code
2017 Leveraging Knowledge Bases in LSTMs for Improving Machine Reading ACL CMU KBMRC paper
2017 World Knowledge for Reading Comprehension: Rare Entity Prediction with Hierarchical LSTMs Using External Descriptions EMNLP McGill University KBMRC paper
2018 QANET: Combining local Convolution with global Self-Attention for Reading Comprehension QANet ICLR CMU, Google Brain SQuAD 1.1 paper, code
2018 Knowledgeable Reader: Enhancing Cloze-Style Reading Comprehension with External Commonsense Knowledge ACL Heidelberg University KBMRC paper
2019 BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding BERT NAACL Google AI Language GLUE, SQuAD 1.1, SQuAD 2.0, SWAG paper, code
2019 Knowledge Based Machine Reading Comprehension Harbin Institute, MRA, ... KBMRC paper
2019 Explicit Utilization of General Knowledge in Machine Reading Comprehension York University KBMRC paper
paper

Datasets

  • Following Danqi Chen, we have four answer types: Cloze test, Multiple choice, Span extraction and Free answering.
Year Dataset Task Size Source Web/Paper Answer type Misc Similar datasets
1999 DeepRead RC 60 development and 60 test? news stories paper Free answering
2013 QA4MRE RC various articles paper Multiple choice
2013 MCTest RC 500 stories + 2k questions fictional stories paper Multiple choice open-domain
2015 CNN and Daily Mail RC 93k + 220k articles CNN + Daily Mail paper Cloze test
2015 bAbI RC classic text adventure game web Free answering 20 tasks
2015 Children's Book Test RC 108 children's books web Cloze test
2016 LAMBADA paper Cloze test
2016 Who-did-What paper Cloze test
2016 MS MARCO web Free answering
2016 NewsQA paper Span extraction
2016 SQuAD 1.1 RC Wikipedia paper Span extraction NewsQA
2017 TriviaQA paper Span extraction
2017 RACE paper Multiple choice
2017 SQA paper
2017 NarrativeQA paper Free answering
2017 SearchQA paper Free answering
2017 WikiSuggest paper
2018 MultiRC RC 6k+ questions various articles web, paper Multiple choice multiple sentence reasoning MCTest
2018 CSQA QA 200k dialogs, 1.6M turns paper
2018 CQA paper
2018 SQuAD 2.0 RC 150k Wikipedia paper Span extraction no answer: 50k NewsQA
2018 CoQA RC 127k various articles paper Free answering conversational questions QuAC
2018 Quac RC 100k Wikipedia paper Span extraction conversational questions CoQA
2018 HotpotQA RC 113k Wikipedia web, paper Span extraction multi-hop reasoning QAngaroo
2018 SWAG QA 113k video caption Multiple choice situational commonsense reasoning
2018 OpenBookQA QA 6k science facts Multiple choice external knowledge ARC
2018 RecipeQA RC 36k various multimodal comprehension
2018 CLOTH RC 99k English exams Cloze test RACE
2018 DuoRC RC 186k movie plot Span extraction NarrativeQA
2018 CliCR RC 100k clinical case text Cloze test
2018 FEVER
2018 ProPara RC 2k procedural text bAbI, SCoNE
2018 ARC RC 8k science exam easy 5197, challenge 2590
2018 DuReader Free answering

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