🧑‍🔬 Who cites Mete Ismayilzada

174 citations of their works from 174 papers of our library (of the 141,840 whose bibliographies we read) · 25 with a page here, the most cited first · ← Mete Ismayilzada

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
1. Self-RAG: Learning to Retrieve, Generate, and Critique through Self-ReflectionarXiv:2310.11511Akari Asai, Zeqiu Wu, Yizhong Wang, et al.2023 · 662 citations
2. 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
3. Large Language Models Cannot Self-Correct Reasoning YetarXiv:2310.01798Jie Huang, Xinyun Chen, Swaroop Mishra, et al.2023 · 396 citations
4. Fine-Grained Human Feedback Gives Better Rewards for Language Model TrainingarXiv:2306.01693Zeqiu Wu, Yushi Hu, Weijia Shi, et al.2023 · 212 citations
5. LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation MethodsarXiv:2412.05579Haitao Li, Qian Dong, Junjie Chen, et al.2024 · 189 citations
   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
6. Reasoning with Language Model Prompting: A SurveyarXiv:2212.09597Shuofei Qiao, Yixin Ou, Ningyu Zhang, et al.2022 · 161 citations
   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
7. Training Language Models to Self-Correct via Reinforcement LearningarXiv:2409.12917Aviral Kumar, Vincent Zhuang, Rishabh Agarwal, et al.2024 · 151 citations
   Self-Evaluation Guided Beam Search for ReasoningConference on Neural Information Processing Systems (NeurIPS)Yuxi Xie, Kenji Kawaguchi, Yiran Zhao, et al.2023 · 145 citations
   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
   Deductive Verification of Chain-of-Thought ReasoningConference on Neural Information Processing Systems (NeurIPS)Zhan Ling, Yunhao Fang, Xuanlin Li, et al.2023 · 128 citations
8. Olmo 3arXiv:2512.13961Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.2025 · 109 citations
   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
9. TextGrad: Automatic "Differentiation" via TextarXiv:2406.07496Mert Yuksekgonul, Federico Bianchi, Joseph Boen, et al.2024 · 88 citations
   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
   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
   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
   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
   Estonian WinoGrande Dataset: Comparative Analysis of LLM Performance on Human and Machine TranslationLanguage Resources and Evaluation Conference (LREC)Marii Ojastu, Hele-Andra Kuulmets, Aleksei Dorkin, et al.2026 · 3 citations
   Are the LLMs Capable of Maintaining at Least the Language Genus?Language Resources and Evaluation Conference (LREC)Sandra Mitrović, David Kletz, Ljiljana Dolamic, et al.2026
   EIFFEL: a novel benchmark to measure bias of English heavy training on French idiomatic expressionsAnnual Meeting of the Association for Computational Linguistics (ACL)Charlotte Noel, Nicholas Asher, Olivier Gouvert, et al.2026
   Is Biomedical Specialization Still Worth It? Insights from Domain-Adaptive Language Modelling with a New French Health CorpusLanguage Resources and Evaluation Conference (LREC)Aidan Mannion, Cécile Macaire, Armand Violle, et al.2026
   Why do Large Language Models Fail in Low-resource Translation? Unraveling the Token Dynamics of Large Language Models for Machine TranslationAnnual Conference of the European Association for Machine Translation (EAMT)Shenbin Qian, Yves Scherrer2026

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