🔗 Who cites «Efficient and Robust Question Answering from Minimal Context over Documents»

51 papers of our library cite it (of the 141,840 whose bibliographies we read) · 10 with a page here, the most cited first · ← back to «Efficient and Robust Question Answering from Minimal Context over Documents»

Multi-hop Reading Comprehension through Question Decomposition and RescoringAnnual Meeting of the Association for Computational Linguistics (ACL)Sewon Min, Victor Zhong, Luke Zettlemoyer, et al.2019 · 306 citations
1. Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question AnsweringarXiv:1911.10470Akari Asai, Kazuma Hashimoto, Hannaneh Hajishirzi, et al.2019 · 272 citations
   Hierarchical Graph Network for Multi-hop Question AnsweringConference on Empirical Methods in Natural Language Processing (EMNLP)Yuwei Fang, Siqi Sun, Zhe Gan, et al.2020 · 241 citations
   Dynamically Fused Graph Network for Multi-hop ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Lin Qiu, Yunxuan Xiao, Yanru Qu, et al.2019 · 237 citations
2. How Context Affects Language Models' Factual PredictionsarXiv:2005.04611Fabio Petroni, Patrick Lewis, Aleksandra Piktus, et al.2020 · 231 citations
   Real-Time Open-Domain Question Answering with Dense-Sparse Phrase IndexAnnual Meeting of the Association for Computational Linguistics (ACL)Minjoon Seo, Jinhyuk Lee, Tom Kwiatkowski, et al.2019 · 216 citations
   Unsupervised Question Answering by Cloze TranslationAnnual Meeting of the Association for Computational Linguistics (ACL)Patrick Lewis, Ludovic Denoyer, Sebastian Riedel2019 · 192 citations
   What Makes Reading Comprehension Questions Easier?Conference on Empirical Methods in Natural Language Processing (EMNLP)Saku Sugawara, Kentaro Inui, Satoshi Sekine, et al.2018 · 178 citations
   Look at the First Sentence: Position Bias in Question AnsweringConference on Empirical Methods in Natural Language Processing (EMNLP)Miyoung Ko, Jinhyuk Lee, Hyunjae Kim, et al.2020 · 102 citations
3. Beyond Leaderboards: A survey of methods for revealing weaknesses in Natural Language Inference data and modelsarXiv:2005.14709Viktor Schlegel, Goran Nenadic, Riza Batista-Navarro2020 · 24 citations

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

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