🧑‍🔬 Who cites Yiran Zhao

273 citations of their works from 264 papers of our library (of the 141,840 whose bibliographies we read) · 18 with a page here, the most cited first · ← Yiran Zhao

1. 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
2. Self-RAG: Learning to Retrieve, Generate, and Critique through Self-ReflectionarXiv:2310.11511Akari Asai, Zeqiu Wu, Yizhong Wang, et al.2023 · 662 citations
3. s1: Simple test-time scalingConference on Empirical Methods in Natural Language Processing (EMNLP)Niklas Muennighoff, Zitong Yang, Weijia Shi, et al.2025 · 584 citations
4. C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation ModelsarXiv:2305.08322Yuzhen Huang, Yuzhuo Bai, Zhihao Zhu, et al.2023 · 428 citations
5. MAmmoTH: Building Math Generalist Models through Hybrid Instruction TuningarXiv:2309.05653Xiang Yue, Xingwei Qu, Ge Zhang, et al.2023 · 288 citations
6. LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation MethodsarXiv:2412.05579Haitao Li, Qian Dong, Junjie Chen, et al.2024 · 189 citations
7. 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
8. 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
9. 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
10. Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language ModelsarXiv:2408.00724Yangzhen Wu, Zhiqing Sun, Shanda Li, et al.2024 · 114 citations
11. Language Ranker: A Metric for Quantifying LLM Performance Across High and Low-Resource LanguagesProceedings of the AAAI Conference on Artificial IntelligenceZihao Li, Yucheng Shi, Zirui Liu, et al.2024 · 95 citations
12. 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
13. 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
14. Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time ScalingarXiv:2502.06703Runze Liu, Junqi Gao, Jian Zhao, et al.2025 · 41 citations
15. Comparative Study of Multilingual Idioms and Similes in Large Language ModelsInternational Conference on Computational Linguistics (COLING)Paria Khoshtab, Danial Namazifard, Mostafa Masoudi, et al.2025 · 14 citations
16. Mind the Gap... or Not? How Translation Errors and Evaluation Details Skew Multilingual ResultsWorkshop on Generation, Evaluation and Metrics (GEM)Jan-Thorsten Peter, David Vilar, Tobias Domhan, et al.2026 · 4 citations
17. Prompting Instruction-tuned LLMs for Semantic Similarity ValuesLanguage Resources and Evaluation Conference (LREC)Xander Akiko Snelder, Yunchong Huang, Jelke Bloem2026 · 2 citations
18. Recent Advances in Text-attributed Graph Learning via Large Models (大模型驱动的文本属性图学习研究进展)Acta Automatica Sinica (自动化学报)Yanping Zheng (郑艳萍), Jiarui Ji (季嘉蕊), Yuwei Hu (胡雨韦), et al.2026

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