---
title: "Who cites Reframing Human-AI — 104 citing papers"
description: "104 papers of the Elamur Research library cite «Reframing Human-AI Collaboration for Generating Free-Text Explanations», found in their…"
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# 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»](https://md.research.elamur.ai/free/en/papers/wiegreffe-2021-reframing-human-ai-collaboration-generating/)

1. [**Chain-of-Thought Prompting Elicits Reasoning in Large Language Models arXiv:2201.11903**Jason Wei, Xuezhi Wang, Dale Schuurmans, et al.*2022 · 11,499 citations*](https://md.research.elamur.ai/free/en/papers/wei-2022-chain-thought-prompting-elicits-reasoning/)
2. **[Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them](https://md.research.elamur.ai/free/en/papers/suzgun-2023-challenging-big-bench-tasks-whether/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mirac Suzgun, Nathan Scales, Nathanael Schärli, et al.*2023 · 1,119 citations*
3. **[Can Large Language Models Transform Computational Social Science?](https://md.research.elamur.ai/free/en/papers/ziems-2023-large-language-models-transform-computational/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Caleb Ziems, William Held, Omar Shaikh, et al.*2023 · 790 citations*
4. **[Towards Reasoning in Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/huang-2023-reasoning-large-language-models-survey/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jie Huang, Kevin Chen-Chuan Chang*2023 · 780 citations*
5. **[Instruction Tuning for Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/zhang-2023-instruction-tuning-large-language-models/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Shengyu Zhang, Linfeng Dong, Xiaoya Li, et al.*2023 · 520 citations*
6. **[Can language models learn from explanations in context?](https://md.research.elamur.ai/free/en/papers/lampinen-2022-can-language-models-learn-explanations/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Andrew Lampinen, Ishita Dasgupta, Stephanie Chan, et al.*2022 · 295 citations*
7. **[Text Classification via Large Language Models](https://md.research.elamur.ai/free/en/papers/sun-2023-text-classification-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiaofei Sun, Xiaoya Li, Jiwei Li, et al.*2023 · 292 citations*
8. **[Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias](https://md.research.elamur.ai/free/en/papers/yu-2023-large-language-model-attributed-training/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yue Yu, Yuchen Zhuang, Jieyu Zhang, et al.*2023 · 202 citations*
9. **[The Unreliability of Explanations in Few-shot Prompting for Textual Reasoning](https://md.research.elamur.ai/free/en/papers/ye-2022-unreliability-explanations-few-shot-prompting/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xi Ye, Greg Durrett*2022 · 196 citations*
10. **[ToolQA: A Dataset for LLM Question Answering with External Tools](https://md.research.elamur.ai/free/en/papers/zhuang-2023-toolqa-dataset-llm-question-answering/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuchen Zhuang, Yue Yu, Kuan Wang, et al.*2023 · 182 citations*
11. [**Reasoning with Language Model Prompting: A Survey arXiv:2212.09597**Shuofei Qiao, Yixin Ou, Ningyu Zhang, et al.*2022 · 161 citations*](https://md.research.elamur.ai/free/en/papers/qiao-2022-reasoning-language-model-prompting-survey/)
12. **[SCOTT: Self-Consistent Chain-of-Thought Distillation](https://md.research.elamur.ai/free/en/papers/wang-2023-scott-self-consistent-chain-thought/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peifeng Wang, Zhengyang Wang, Zheng Li, et al.*2023 · 146 citations*
13. **[Verify-and-Edit: A Knowledge-Enhanced Chain-of-Thought Framework](https://md.research.elamur.ai/free/en/papers/zhao-2023-verify-edit-knowledge-enhanced-chain/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/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-Step](https://md.research.elamur.ai/free/en/papers/li-2023-symbolic-chain-thought-distillation-small/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Liunian Harold Li, Jack Hessel, Youngjae Yu, et al.*2023 · 140 citations*
15. **[Few-Shot Self-Rationalization with Natural Language Prompts](https://md.research.elamur.ai/free/en/papers/marasovic-2022-few-shot-self-rationalization-natural/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ana Marasovic, Iz Beltagy, Doug Downey, et al.*2022 · 134 citations*
16. **[FLUTE: Figurative Language Understanding through Textual Explanations](https://md.research.elamur.ai/free/en/papers/chakrabarty-2022-flute-figurative-language-understanding-through/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tuhin Chakrabarty, Arkadiy Saakyan, Debanjan Ghosh, et al.*2022 · 133 citations*
17. [**Explanations from Large Language Models Make Small Reasoners Better arXiv:2210.06726**Shiyang Li, Jianshu Chen, Yelong Shen, et al.*2022 · 120 citations*](https://md.research.elamur.ai/free/en/papers/li-2022-explanations-large-language-models-make/)
18. **[Do Androids Laugh at Electric Sheep? Humor “Understanding” Benchmarks from The New Yorker Caption Contest](https://md.research.elamur.ai/free/en/papers/hessel-2023-do-androids-laugh-electric-sheep/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jack Hessel, Ana Marasovic, Jena D. Hwang, et al.*2023 · 112 citations*
19. [**Rationale-Augmented Ensembles in Language Models arXiv:2207.00747**Xuezhi Wang, Jason Wei, Dale Schuurmans, et al.*2022 · 101 citations*](https://md.research.elamur.ai/free/en/papers/wang-2022-rationale-augmented-ensembles-language-models/)
20. **[What happens before and after: Multi-Event Commonsense in Event Coreference Resolution](https://md.research.elamur.ai/free/en/papers/ravi-2023-what-happens-before-after-multi/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Sahithya Ravi, Chris Tanner, Raymond Ng, et al.*2023 · 21 citations*
21. **[Ecologically Valid Explanations for Label Variation in NLI](https://md.research.elamur.ai/free/en/papers/jiang-2023-ecologically-valid-explanations-label-variation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nan-Jiang Jiang, Chenhao Tan, Marie-Catherine de Marneffe*2023 · 19 citations*
22. **[Okay, Let's Do This! Modeling Event Coreference with Generated Rationales and Knowledge Distillation](https://md.research.elamur.ai/free/en/papers/nath-2024-okay-let-s-do-this/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Abhijnan Nath, Shadi Manafi Avari, Avyakta Chelle, et al.*2024 · 16 citations*
23. **[Understanding Figurative Meaning through Explainable Visual Entailment](https://md.research.elamur.ai/free/en/papers/saakyan-2025-understanding-figurative-meaning-through-explainable/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/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\](https://md.research.elamur.ai/free/en/papers/kavumba-2023-prompting-explanations-improves-adversarial-nli/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Pride Kavumba, Ana Brassard, Benjamin Heinzerling, et al.*2023 · 14 citations*
25. **[Tailoring Self-Rationalizers with Multi-Reward Distillation](https://md.research.elamur.ai/free/en/papers/ramnath-2023-tailoring-self-rationalizers-multi-reward/) [International Conference on Learning Representations (ICLR)](https://md.research.elamur.ai/free/en/venues/international-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 NLI](https://md.research.elamur.ai/free/en/papers/chen-2025-rose-any-other-name-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Beiduo Chen, Siyao Peng, Anna Korhonen, et al.*2025 · 9 citations*
27. [**Understanding and Predicting Human Label Variation in Natural Language Inference through Explanation arXiv:2304.12443**Nan-Jiang Jiang, Chenhao Tan, Marie-Catherine de Marneffe*2023 · 8 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2023-understanding-predicting-human-label-variation/)
28. **[Label and Explanation Variation in LLM-Based Annotation: a Case Study in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/kulmizev-2026-label-explanation-variation-llm-based/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Artur Kulmizev, Erika Lombart, Patrick Watrin, et al.*2026 · 2 citations*
29. [**Hypothesis-only Biases in Large Language Model-Elicited Natural Language Inference arXiv:2410.08996**Grace Proebsting, Adam Poliak*2024 · 2 citations*](https://md.research.elamur.ai/free/en/papers/proebsting-2024-hypothesis-only-biases-large-language/)
30. **[Biases in Large Language Model-Elicited Text: A Case Study in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/proebsting-2025-biases-large-language-model-elicited/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Grace Proebsting, Adam Poliak*2025 · 1 citation*
31. **[Arguments that Alter Minds: LLM Rationales Sway Human (and LLM) Notions of Plausibility](https://md.research.elamur.ai/free/en/papers/palta-2026-arguments-that-alter-minds-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shramay Palta, Peter A. Rankel, Sarah Wiegreffe, et al.*2026*
32. **[IDEAlign: Comparing Ideas of Large Language Models to Domain Experts](https://md.research.elamur.ai/free/en/papers/nam-2026-idealign-comparing-ideas-large-language/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**HyunJi Nam, Lucía Langlois, Jim Malamut, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/wiegreffe-2021-reframing-human-ai-collaboration-generating/) — Reframing Human-AI Collaboration for Generating Free-Text Explanations