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Chandra Bhagavatula — all works

31 works · ← Chandra Bhagavatula

  1. WinoGrande: An Adversarial Winograd Schema Challenge at Scale ↗arXiv:1907.10641 · no summary yetKeisuke Sakaguchi et al.2019 · 1,913 citations
  2. Cosmos QA: Machine Reading Comprehension with Contextual Commonsense ReasoningLifu Huang, Ronan Le Bras, Chandra Bhagavatula, et al.English · 544 citations
  3. CommonGen: A Constrained Text Generation Challenge for Generative Commonsense Reasoning ↗Findings of the Association for Computational Linguistics: EMNLP 2020 · no summary yetBill Yuchen Lin et al.2020 · 437 citations
  4. Unsupervised Commonsense Question Answering with Self-Talk ↗Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) · no summary yetVered Shwartz et al.2020 · 322 citations
  5. Abductive Commonsense ReasoningChandra Bhagavatula, Ronan Le Bras, Chaitanya Malaviya, et al.English · 309 citations
  6. COMET-ATOMIC 2020: On Symbolic and Neural Commonsense Knowledge GraphsJena D. Hwang, Chandra Bhagavatula, Ronan Le Bras, et al.Mova's core list · 239 citations
  7. Generative Data Augmentation for Commonsense ReasoningFindings of the Association for Computational LinguisticsYiben Yang, Chaitanya Malaviya, Jared Fernandez, et al.2020 · 198 citations
  8. Content-Based Citation Recommendation ↗Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers) · no summary yetChandra Bhagavatula et al.2018 · 196 citations
  9. Counterfactual Story Reasoning and Generation ↗Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) · no summary yetLianhui Qin et al.2019 · 187 citations
  10. The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context LearningarXiv:2312.01552Bill Yuchen Lin, Abhilasha Ravichander, Ximing Lu, et al.2023 · 150 citations
  11. Thinking Like a Skeptic: Defeasible Inference in Natural Language ↗Findings of the Association for Computational Linguistics: EMNLP 2020 · no summary yetRachel Rudinger et al.2020 · 137 citations
  12. Can Machines Learn Morality? The Delphi ExperimentarXiv:2110.07574Liwei Jiang, Jena D. Hwang, Chandra Bhagavatula, et al.2021 · 110 citations
  13. CommonsenseQA 2.0: Exposing the Limits of AI through GamificationarXiv:2201.05320Alon Talmor, Ori Yoran, Ronan Le Bras, et al.2022 · 94 citations
  14. The AI2 system at SemEval-2017 Task 10 (ScienceIE): semi-supervised end-to-end entity and relation extraction ↗Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017) · no summary yetWaleed Ammar et al.2017 · 72 citations
  15. Natural Language Rationales with Full-Stack Visual Reasoning: From Pixels to Semantic Frames to Commonsense Graphs ↗Findings of the Association for Computational Linguistics: EMNLP 2020 · no summary yetAna Marasović et al.2020 · 65 citations
  16. Phenomenal Yet Puzzling: Testing Inductive Reasoning Capabilities of Language Models with Hypothesis Refinement ↗arXiv (Cornell University) · no summary yetLinlu Qiu et al.2023 · 64 citations
  17. Investigating machine moral judgement through the Delphi experiment ↗Nature Machine Intelligence · no summary yetLiwei Jiang et al.2025 · 44 citations
  18. “You Are An Expert Linguistic Annotator”: Limits of LLMs as Analyzers of Abstract Meaning Representation ↗Findings of the Association for Computational Linguistics: EMNLP 2023 · no summary yetAllyson Ettinger et al.2023 · 32 citations
  19. Penguins Don't Fly: Reasoning about Generics through Instantiations and Exceptions ↗Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics · no summary yetEmily Allaway et al.2023 · 31 citations
  20. PlaSma: Making Small Language Models Better Procedural Knowledge Models for (Counterfactual) PlanningarXiv:2305.19472Faeze Brahman, Chandra Bhagavatula, Valentina Pyatkin, et al.2023 · 25 citations
  21. Exceptions, Instantiations, and Overgeneralization: Insights into How Language Models Process Generics ↗Computational Linguistics · no summary yetEmily Allaway et al.2024 · 13 citations

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