---
title: "Yejin Choi — papers of 2019 — 11 papers, the most cited first"
description: "Yejin Choi — papers of 2019: 11 papers on Elamur Research, the most cited first — what each work is about in our own words."
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# Yejin Choi — papers of 2019 — 11 papers, the most cited first

11 papers · [all years of Yejin Choi](https://md.research.elamur.ai/free/en/authors/yejin-choi/#years)

- [The Curious Case of Neural Text Degeneration arXiv:1904.09751](https://md.research.elamur.ai/free/en/papers/holtzman-2019-curious-case-neural-text-degeneration/) — Ari Holtzman, Jan Buys, Li Du, et al. · 2019 · 2,660 citations

**[COMET: Commonsense Transformers for Automatic Knowledge Graph Construction](https://md.research.elamur.ai/free/en/papers/bosselut-2019-comet-commonsense-transformers-automatic-knowledge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Antoine Bosselut, Hannah Rashkin, Maarten Sap, et al.*2019 · 1,294 citations*

**[PIQA: Reasoning about Physical Commonsense in Natural Language](https://md.research.elamur.ai/free/en/papers/bisk-2019-piqa-reasoning-about-physical-commonsense/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Yonatan Bisk, Rowan Zellers, Ronan Le Bras, et al.*2019 · 1,264 citations*

**[The Risk of Racial Bias in Hate Speech Detection](https://md.research.elamur.ai/free/en/papers/sap-2019-risk-racial-bias-hate-speech/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Maarten Sap, Dallas Card, Saadia Gabriel, et al.*2019 · 1,164 citations*

- [Cosmos QA: Machine Reading Comprehension with Contextual Commonsense Reasoning](https://md.research.elamur.ai/free/en/papers/huang-2019-cosmos-qa-machine-reading-comprehension/) — Lifu Huang, Ronan Le Bras, Chandra Bhagavatula, et al. · English · 544 citations

**[MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms](https://md.research.elamur.ai/free/en/papers/amini-2019-mathqa-interpretable-math-word-problem/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Aida Amini, Saadia Gabriel, Shanchuan Lin, et al.*2019 · 507 citations*

- [Defending Against Neural Fake News arXiv:1905.12616](https://md.research.elamur.ai/free/en/papers/zellers-2019-defending-against-neural-fake-news/) — Rowan Zellers, Ari Holtzman, Hannah Rashkin, et al. · 2019 · 478 citations

**[DREAM: A Challenge Data Set and Models for Dialogue-Based Reading Comprehension](https://md.research.elamur.ai/free/en/papers/sun-2019-dream-challenge-data-set-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Kai Sun, Dian Yu, Jianshu Chen, et al.*2019 · 334 citations*

- [Abductive Commonsense Reasoning](https://md.research.elamur.ai/free/en/papers/bhagavatula-2019-abductive-commonsense-reasoning/) — Chandra Bhagavatula, Ronan Le Bras, Chaitanya Malaviya, et al. · English · 309 citations
- [SocialIQA: Commonsense Reasoning about Social Interactions arXiv:1904.09728](https://md.research.elamur.ai/free/en/papers/sap-2019-socialiqa-commonsense-reasoning-about-social/) — Maarten Sap, Hannah Rashkin, Derek Chen, et al. · 2019 · 259 citations
- [Do Neural Language Representations Learn Physical Commonsense? arXiv:1908.02899](https://md.research.elamur.ai/free/en/papers/forbes-2019-do-neural-language-representations-learn/) — Maxwell Forbes, Ari Holtzman, Yejin Choi · 2019 · 64 citations