🔗 Who cites «Reframing Human-AI Collaboration for Generating Free-Text Explanations»

104 papers of our library cite it (of the 149,439 whose bibliographies we read) · 32 with a page here, the most cited first · ← back to «Reframing Human-AI Collaboration for Generating Free-Text Explanations»

1. Chain-of-Thought Prompting Elicits Reasoning in Large Language ModelsarXiv:2201.11903Jason Wei, Xuezhi Wang, Dale Schuurmans, et al.2022 · 11,499 citations
2. Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve ThemFindings of the Association for Computational LinguisticsMirac Suzgun, Nathan Scales, Nathanael Schärli, et al.2023 · 1,119 citations
3. Can Large Language Models Transform Computational Social Science?Computational LinguisticsCaleb Ziems, William Held, Omar Shaikh, et al.2023 · 790 citations
4. Towards Reasoning in Large Language Models: A SurveyFindings of the Association for Computational LinguisticsJie Huang, Kevin Chen-Chuan Chang2023 · 780 citations
5. Instruction Tuning for Large Language Models: A SurveyACM Computing SurveysShengyu Zhang, Linfeng Dong, Xiaoya Li, et al.2023 · 520 citations
6. Can language models learn from explanations in context?Findings of the Association for Computational LinguisticsAndrew Lampinen, Ishita Dasgupta, Stephanie Chan, et al.2022 · 295 citations
7. Text Classification via Large Language ModelsFindings of the Association for Computational LinguisticsXiaofei Sun, Xiaoya Li, Jiwei Li, et al.2023 · 292 citations
8. Large Language Model as Attributed Training Data Generator: A Tale of Diversity and BiasConference on Neural Information Processing Systems (NeurIPS)Yue Yu, Yuchen Zhuang, Jieyu Zhang, et al.2023 · 202 citations
9. The Unreliability of Explanations in Few-shot Prompting for Textual ReasoningConference on Neural Information Processing Systems (NeurIPS)Xi Ye, Greg Durrett2022 · 196 citations
10. ToolQA: A Dataset for LLM Question Answering with External ToolsConference on Neural Information Processing Systems (NeurIPS)Yuchen Zhuang, Yue Yu, Kuan Wang, et al.2023 · 182 citations
11. Reasoning with Language Model Prompting: A SurveyarXiv:2212.09597Shuofei Qiao, Yixin Ou, Ningyu Zhang, et al.2022 · 161 citations
12. SCOTT: Self-Consistent Chain-of-Thought DistillationAnnual Meeting of the Association for Computational Linguistics (ACL)Peifeng Wang, Zhengyang Wang, Zheng Li, et al.2023 · 146 citations
13. Verify-and-Edit: A Knowledge-Enhanced Chain-of-Thought FrameworkAnnual Meeting of the Association for Computational Linguistics (ACL)Ruochen Zhao, Xingxuan Li, Shafiq Joty, et al.2023 · 145 citations
14. Symbolic Chain-of-Thought Distillation: Small Models Can Also “Think” Step-by-StepAnnual Meeting of the Association for Computational Linguistics (ACL)Liunian Harold Li, Jack Hessel, Youngjae Yu, et al.2023 · 140 citations
15. Few-Shot Self-Rationalization with Natural Language PromptsFindings of the Association for Computational LinguisticsAna Marasovic, Iz Beltagy, Doug Downey, et al.2022 · 134 citations
16. FLUTE: Figurative Language Understanding through Textual ExplanationsConference on Empirical Methods in Natural Language Processing (EMNLP)Tuhin Chakrabarty, Arkadiy Saakyan, Debanjan Ghosh, et al.2022 · 133 citations
17. Explanations from Large Language Models Make Small Reasoners BetterarXiv:2210.06726Shiyang Li, Jianshu Chen, Yelong Shen, et al.2022 · 120 citations
18. Do Androids Laugh at Electric Sheep? Humor “Understanding” Benchmarks from The New Yorker Caption ContestAnnual Meeting of the Association for Computational Linguistics (ACL)Jack Hessel, Ana Marasovic, Jena D. Hwang, et al.2023 · 112 citations
19. Rationale-Augmented Ensembles in Language ModelsarXiv:2207.00747Xuezhi Wang, Jason Wei, Dale Schuurmans, et al.2022 · 101 citations
20. What happens before and after: Multi-Event Commonsense in Event Coreference ResolutionConference of the European Chapter of the Association for Computational Linguistics (EACL)Sahithya Ravi, Chris Tanner, Raymond Ng, et al.2023 · 21 citations
21. Ecologically Valid Explanations for Label Variation in NLIFindings of the Association for Computational LinguisticsNan-Jiang Jiang, Chenhao Tan, Marie-Catherine de Marneffe2023 · 19 citations
22. Okay, Let's Do This! Modeling Event Coreference with Generated Rationales and Knowledge DistillationConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Abhijnan Nath, Shadi Manafi Avari, Avyakta Chelle, et al.2024 · 16 citations
23. Understanding Figurative Meaning through Explainable Visual EntailmentConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Arkadiy Saakyan, Shreyas Kulkarni, Tuhin Chakrabarty, et al.2025 · 15 citations
24. Prompting for explanations improves Adversarial NLI. Is this true? \Yes\ it is \true\ because ıt weakens superficial cues\Findings of the Association for Computational LinguisticsPride Kavumba, Ana Brassard, Benjamin Heinzerling, et al.2023 · 14 citations
25. Tailoring Self-Rationalizers with Multi-Reward DistillationInternational Conference on Learning Representations (ICLR)Sahana Ramnath, Brihi Joshi, Skyler Hallinan, et al.2023 · 14 citations
26. A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLIFindings of the Association for Computational LinguisticsBeiduo Chen, Siyao Peng, Anna Korhonen, et al.2025 · 9 citations
27. Understanding and Predicting Human Label Variation in Natural Language Inference through ExplanationarXiv:2304.12443Nan-Jiang Jiang, Chenhao Tan, Marie-Catherine de Marneffe2023 · 8 citations
28. Label and Explanation Variation in LLM-Based Annotation: a Case Study in Natural Language InferenceAnnual Meeting of the Association for Computational Linguistics (ACL)Artur Kulmizev, Erika Lombart, Patrick Watrin, et al.2026 · 2 citations
29. Hypothesis-only Biases in Large Language Model-Elicited Natural Language InferencearXiv:2410.08996Grace Proebsting, Adam Poliak2024 · 2 citations
30. Biases in Large Language Model-Elicited Text: A Case Study in Natural Language InferenceInternational Conference on Computational Linguistics (COLING)Grace Proebsting, Adam Poliak2025 · 1 citation
31. Arguments that Alter Minds: LLM Rationales Sway Human (and LLM) Notions of PlausibilityAnnual Meeting of the Association for Computational Linguistics (ACL)Shramay Palta, Peter A. Rankel, Sarah Wiegreffe, et al.2026
32. IDEAlign: Comparing Ideas of Large Language Models to Domain ExpertsConference of the European Chapter of the Association for Computational Linguistics (EACL)HyunJi Nam, Lucía Langlois, Jim Malamut, et al.2026

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