🧑‍🔬 Who cites Boi Faltings

175 citations of their works from 171 papers of our library (of the 141,840 whose bibliographies we read) · 20 with a page here, the most cited first · ← Boi Faltings

1. A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open QuestionsACM Transactions on Information SystemsLei Huang, Weijiang Yu, Weitao Ma, et al.2023 · 3,222 citations
2. Reflexion: Language Agents with Verbal Reinforcement LearningConference on Neural Information Processing Systems (NeurIPS)Noah Shinn, Federico Cassano, Edward Berman, et al.2023 · 2,204 citations
3. Self-RAG: Learning to Retrieve, Generate, and Critique through Self-ReflectionarXiv:2310.11511Akari Asai, Zeqiu Wu, Yizhong Wang, et al.2023 · 662 citations
4. Unleashing the potential of prompt engineering for large language modelsarXiv:2310.14735 · Patterns 6(6) 101,260 (2025)Banghao Chen, Zhaofeng Zhang, Nicolas Langrene, et al.2023 · 536 citations
5. Large Language Models Cannot Self-Correct Reasoning YetarXiv:2310.01798Jie Huang, Xinyun Chen, Swaroop Mishra, et al.2023 · 396 citations
6. Fine-Grained Human Feedback Gives Better Rewards for Language Model TrainingarXiv:2306.01693Zeqiu Wu, Yushi Hu, Weijia Shi, et al.2023 · 212 citations
7. LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation MethodsarXiv:2412.05579Haitao Li, Qian Dong, Junjie Chen, et al.2024 · 189 citations
8. Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language ModelsScience China Information SciencesQiguang Chen, Libo Qin, Jinhao Liu, et al.2025 · 174 citations
9. Reasoning with Language Model Prompting: A SurveyarXiv:2212.09597Shuofei Qiao, Yixin Ou, Ningyu Zhang, et al.2022 · 161 citations
10. When Can LLMs Actually Correct Their Own Mistakes? A Critical Survey of Self-Correction of LLMsTransactions of the Association for Computational Linguistics (TACL)Ryo Kamoi, Yusen Zhang, Nan Zhang, et al.2024 · 159 citations
11. Training Language Models to Self-Correct via Reinforcement LearningarXiv:2409.12917Aviral Kumar, Vincent Zhuang, Rishabh Agarwal, et al.2024 · 151 citations
12. Self-Evaluation Guided Beam Search for ReasoningConference on Neural Information Processing Systems (NeurIPS)Yuxi Xie, Kenji Kawaguchi, Yiran Zhao, et al.2023 · 145 citations
13. Automatically Correcting Large Language Models: Surveying the Landscape of Diverse Automated Correction StrategiesTransactions of the Association for Computational Linguistics (TACL)Liangming Pan, Michael Saxon, Wenda Xu, et al.2024 · 140 citations
14. Deductive Verification of Chain-of-Thought ReasoningConference on Neural Information Processing Systems (NeurIPS)Zhan Ling, Yunhao Fang, Xuanlin Li, et al.2023 · 128 citations
15. Answering Questions by Meta-Reasoning over Multiple Chains of ThoughtConference on Empirical Methods in Natural Language Processing (EMNLP)Ori Yoran, Tomer Wolfson, Ben Bogin, et al.2023 · 97 citations
16. TextGrad: Automatic "Differentiation" via TextarXiv:2406.07496Mert Yuksekgonul, Federico Bianchi, Joseph Boen, et al.2024 · 88 citations
17. LLMs cannot find reasoning errors, but can correct them given the error locationFindings of the Association for Computational LinguisticsGladys Tyen, Hassan Mansoor, Victor Carbune, et al.2024 · 85 citations
18. Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language GenerationTransactions of the Association for Computational Linguistics (TACL)Patrick Fernandes, Aman Madaan, Emmy Liu, et al.2023 · 84 citations
19. Making Reasoning Matter: Measuring and Improving Faithfulness of Chain-of-Thought ReasoningFindings of the Association for Computational LinguisticsDebjit Paul, Robert West, Antoine Bosselut, et al.2024 · 77 citations
20. Self-Contrast: Better Reflection Through Inconsistent Solving PerspectivesAnnual Meeting of the Association for Computational Linguistics (ACL)Wenqi Zhang, Yongliang Shen, Linjuan Wu, et al.2024 · 75 citations

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