🔗 Who cites «What Makes Reading Comprehension Questions Easier?»

73 papers of our library cite it (of the 141,840 whose bibliographies we read) · 14 with a page here, the most cited first · ← back to «What Makes Reading Comprehension Questions Easier?»

MLQA: Evaluating Cross-lingual Extractive Question AnsweringAnnual Meeting of the Association for Computational Linguistics (ACL)Patrick Lewis, Barlas Oğuz, Ruty Rinott, et al.2019 · 738 citations
Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning StepsInternational Conference on Computational Linguistics (COLING)Xanh Ho, Anh-Khoa Duong Nguyen, Saku Sugawara, et al.2020 · 735 citations
Factual Probing Is [MASK]: Learning vs. Learning to RecallConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Zexuan Zhong, Dan Friedman, Danqi Chen2021 · 411 citations
1. Complexity-Based Prompting for Multi-Step ReasoningarXiv:2210.00720Yao Fu, Hao Peng, Ashish Sabharwal, et al.2022 · 343 citations
2. ReClor: A Reading Comprehension Dataset Requiring Logical ReasoningarXiv:2002.04326Weihao Yu, Zihang Jiang, Yanfei Dong, et al.2020 · 285 citations
   Can You Unpack That? Learning to Rewrite Questions-in-ContextConference on Empirical Methods in Natural Language Processing (EMNLP)Ahmed Elgohary, Denis Peskov, Jordan Boyd-Graber2019 · 245 citations
   Compositional Questions Do Not Necessitate Multi-hop ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Sewon Min, Eric Wallace, Sameer Singh, et al.2019 · 231 citations
   Unsupervised Question Answering by Cloze TranslationAnnual Meeting of the Association for Computational Linguistics (ACL)Patrick Lewis, Ludovic Denoyer, Sebastian Riedel2019 · 192 citations
   Improving Machine Reading Comprehension with General Reading StrategiesConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Kai Sun, Dian Yu, Dong Yu, et al.2019 · 172 citations
   Impact of Pretraining Term Frequencies on Few-Shot Numerical ReasoningFindings of the Association for Computational LinguisticsYasaman Razeghi, Robert L Logan IV, Matt Gardner, et al.2022 · 162 citations
   Understanding Dataset Design Choices for Multi-hop ReasoningConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Jifan Chen, Greg Durrett2019 · 146 citations
   Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled DataFindings of the Association for Computational LinguisticsKashun Shum, Shizhe Diao, Tong Zhang2023 · 128 citations
   Logic-Guided Data Augmentation and Regularization for Consistent Question AnsweringAnnual Meeting of the Association for Computational Linguistics (ACL)Akari Asai, Hannaneh Hajishirzi2020 · 111 citations
   An Annotated Corpus of Reference Resolution for Interpreting Common GroundingProceedings of the AAAI Conference on Artificial IntelligenceTakuma Udagawa, Akiko Aizawa2019 · 14 citations

59 more papers of our library cite it; they have no page here yet.

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