--- title: "Who cites Who did What: A Large-Scale — 59 citing papers" description: "59 papers of the Elamur Research library cite «Who did What: A Large-Scale Person-Centered Cloze Dataset», found in their bibliographies…" canonical: "https://research.elamur.ai/free/en/papers/onishi-2016-who-did-what-large-scale/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/onishi-2016-who-did-what-large-scale/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Who did What: A Large-Scale Person-Centered Cloze…](https://md.research.elamur.ai/free/en/papers/onishi-2016-who-did-what-large-scale/) / cited by # Who cites «Who did What: A Large-Scale Person-Centered Cloze Dataset» 59 papers of our library cite it (of the 141,840 whose bibliographies we read) · 19 with a page here, the most cited first · [← back to «Who did What: A Large-Scale Person-Centered Cloze Dataset»](https://md.research.elamur.ai/free/en/papers/onishi-2016-who-did-what-large-scale/) 1. **[Natural Questions: A Benchmark for Question Answering Research](https://md.research.elamur.ai/free/en/papers/kwiatkowski-2019-natural-questions-benchmark-question-answering/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Tom Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, et al.*2019 · 4,035 citations* 2. **[TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension](https://md.research.elamur.ai/free/en/papers/joshi-2017-triviaqa-large-scale-distantly-supervised/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mandar Joshi, Eunsol Choi, Daniel Weld, et al.*2017 · 3,213 citations* 3. [**RACE: Large-scale ReAding Comprehension Dataset From Examinations**Guokun Lai, Qizhe Xie, Hanxiao Liu, et al.*2017 · 1,629 citations*](https://md.research.elamur.ai/free/en/papers/lai-2017-race-large-scale-reading-comprehension/) 4. **[The Web as a Knowledge-Base for Answering Complex Questions](https://md.research.elamur.ai/free/en/papers/talmor-2018-web-as-knowledge-base-answering/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Alon Talmor, Jonathan Berant*2018 · 814 citations* 5. [**SearchQA: A New Q&A Dataset Augmented with Context from a Search Engine arXiv:1704.05179**Matthew Dunn, Levent Sagun, Mike Higgins, et al.*2017 · 547 citations*](https://md.research.elamur.ai/free/en/papers/dunn-2017-searchqa-new-q-dataset-augmented/) 6. **[Crowdsourcing Multiple Choice Science Questions](https://md.research.elamur.ai/free/en/papers/welbl-2017-crowdsourcing-multiple-choice-science-questions/) [Workshop on Noisy User-generated Text](https://md.research.elamur.ai/free/en/venues/wnut/)**Johannes Welbl, Nelson F. Liu, Matt Gardner*2017 · 516 citations* 7. [**How Much Reading Does Reading Comprehension Require? A Critical Investigation of Popular Benchmarks**Divyansh Kaushik, Zachary C. Lipton*2018 · 361 citations*](https://md.research.elamur.ai/free/en/papers/kaushik-2018-how-much-reading-does-reading/) 8. **[Towards Debiasing Fact Verification Models](https://md.research.elamur.ai/free/en/papers/schuster-2019-debiasing-fact-verification-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tal Schuster, Darsh Shah, Yun Jie Serene Yeo, et al.*2019 · 296 citations* 9. **[Constructing Datasets for Multi-hop Reading Comprehension Across Documents](https://md.research.elamur.ai/free/en/papers/welbl-2018-constructing-datasets-multi-hop-reading/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Johannes Welbl, Pontus Stenetorp, Sebastian Riedel*2018 · 284 citations* 10. **[Knowledgeable Reader: Enhancing Cloze-Style Reading Comprehension with External Commonsense Knowledge](https://md.research.elamur.ai/free/en/papers/mihaylov-2018-knowledgeable-reader-enhancing-cloze-style/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Todor Mihaylov, Anette Frank*2018 · 260 citations* 11. **[Dynamically Fused Graph Network for Multi-hop Reasoning](https://md.research.elamur.ai/free/en/papers/qiu-2019-dynamically-fused-graph-network-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lin Qiu, Yunxuan Xiao, Yanru Qu, et al.*2019 · 237 citations* 12. **[DuoRC: Towards Complex Language Understanding with Paraphrased Reading Comprehension](https://md.research.elamur.ai/free/en/papers/saha-2018-duorc-complex-language-understanding-paraphrased/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Amrita Saha, Rahul Aralikatte, Mitesh M. Khapra, et al.*2018 · 189 citations* 13. **[What Makes Reading Comprehension Questions Easier?](https://md.research.elamur.ai/free/en/papers/sugawara-2018-what-makes-reading-comprehension-questions/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Saku Sugawara, Kentaro Inui, Satoshi Sekine, et al.*2018 · 178 citations* 14. **[Improving Machine Reading Comprehension with General Reading Strategies](https://md.research.elamur.ai/free/en/papers/sun-2019-improving-machine-reading-comprehension-general/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Kai Sun, Dian Yu, Dong Yu, et al.*2019 · 172 citations* 15. **[Speak, Memory: An Archaeology of Books Known to ChatGPT/GPT-4](https://md.research.elamur.ai/free/en/papers/chang-2023-speak-memory-archaeology-books-known/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kent K. Chang, Mackenzie Cramer, Sandeep Soni, et al.*2023 · 166 citations* 16. **[Question Answering for Privacy Policies: Combining Computational and Legal Perspectives](https://md.research.elamur.ai/free/en/papers/ravichander-2019-question-answering-privacy-policies-combining/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Abhilasha Ravichander, Alan W Black, Shomir Wilson, et al.*2019 · 163 citations* 17. **[ChID: A Large-scale Chinese IDiom Dataset for Cloze Test](https://md.research.elamur.ai/free/en/papers/zheng-2019-chid-large-scale-chinese/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chujie Zheng, Minlie Huang, Aixin Sun*2019 · 119 citations* 18. [**English Machine Reading Comprehension Datasets: A Survey**Daria Dzendzik, Jennifer Foster, Carl Vogel*2021 · 54 citations*](https://md.research.elamur.ai/free/en/papers/dzendzik-2021-english-machine-reading-comprehension-datasets/) 19. [**Multi-Relational Question Answering from Narratives: Machine Reading and Reasoning in Simulated Worlds**Igor Labutov, Bishan Yang, Anusha Prakash, et al.*2018 · 17 citations*](https://md.research.elamur.ai/free/en/papers/labutov-2018-multi-relational-question-answering-narratives/) 40 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/onishi-2016-who-did-what-large-scale/) — Who did What: A Large-Scale Person-Centered Cloze Dataset