🧑‍🔬 Who cites Yile Wang

429 citations of their works from 428 papers of our library (of the 141,840 whose bibliographies we read) · 35 with a page here, the most cited first · ← Yile Wang

1. Training Verifiers to Solve Math Word ProblemsarXiv:2110.14168Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, et al.2021 · 3,680 citations
2. 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
3. Measuring Mathematical Problem Solving With the MATH DatasetarXiv:2103.03874Dan Hendrycks, Collin Burns, Saurav Kadavath, et al.2021 · 2,320 citations
4. Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language modelsarXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5BvosjAarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.2022 · 1,703 citations
5. Retrieval-Augmented Generation for Large Language Models: A SurveyarXiv:2312.10997Yunfan Gao, Yun Xiong, Xinyu Gao, et al.2023 · 1,648 citations
6. A Comprehensive Overview of Large Language ModelsACM Transactions on Intelligent Systems and TechnologyHumza Naveed, Asad Ullah Khan, Shi Qiu, et al.2023 · 1,286 citations
7. A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language ModelsACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)Wenqi Fan; Yujuan Ding; Liangbo Ning; Shijie Wang; Hengyun Li; Dawei Yin; Tat-Seng Chua;, Qing Li2024 · 1,006 citations
8. GPT-NeoX-20B: An Open-Source Autoregressive Language ModelBigScience Episode – Workshop on Challenges & Perspectives in Creating Large Language ModelsSidney Black, Stella Biderman, Eric Hallahan, et al.2022 · 821 citations
9. s1: Simple test-time scalingConference on Empirical Methods in Natural Language Processing (EMNLP)Niklas Muennighoff, Zitong Yang, Weijia Shi, et al.2025 · 584 citations
10. AGIEval: A Human-Centric Benchmark for Evaluating Foundation ModelsFindings of the Association for Computational LinguisticsWanjun Zhong, Ruixiang Cui, Yiduo Guo, et al.2024 · 564 citations
11. Measuring Coding Challenge Competence With APPSarXiv:2105.09938Dan Hendrycks, Steven Basart, Saurav Kadavath, et al.2021 · 439 citations
12. Large Language Models for Information Retrieval: A SurveyACM Transactions on Information SystemsYutao Zhu; Huaying Yuan; Shuting Wang; Jiongnan Liu; Wenhan Liu; Chenlong Deng; Haonan Chen; Zheng Liu; Zhicheng Dou;, Ji-Rong Wen2023 · 335 citations
13. Large Language Models are Better Reasoners with Self-VerificationFindings of the Association for Computational LinguisticsYixuan Weng, Minjun Zhu, Fei Xia, et al.2023 · 302 citations
14. The Effect of Sampling Temperature on Problem Solving in Large Language ModelsFindings of the Association for Computational LinguisticsMatthew Renze2024 · 262 citations
15. Measuring Faithfulness in Chain-of-Thought ReasoningarXiv:2307.13702Tamera Lanham, Anna Chen, Ansh Radhakrishnan, et al.2023 · 249 citations
16. FOLIO: Natural Language Reasoning with First-Order LogicarXiv:2209.00840Simeng Han, Hailey Schoelkopf, Yilun Zhao, et al.2022 · 217 citations
17. Making Language Models Better Reasoners with Step-Aware VerifierAnnual Meeting of the Association for Computational Linguistics (ACL)Yifei Li, Zeqi Lin, Shizhuo Zhang, et al.2023 · 216 citations
18. Evaluating Large Language Models: A Comprehensive SurveyarXiv:2310.19736Zishan Guo, Renren Jin, Chuang Liu, et al.2023 · 178 citations
19. Leveraging Large Language Models for Multiple Choice Question AnsweringarXiv:2210.12353Joshua Robinson, Christopher Michael Rytting, David Wingate2022 · 157 citations
20. DataComp-LM: In search of the next generation of training sets for language modelsConference on Neural Information Processing Systems (NeurIPS)Jeffrey Li, Alex Fang, Georgios Smyrnis, et al.2024 · 156 citations
21. Are Large Language Models Really Good Logical Reasoners? A Comprehensive Evaluation and BeyondIEEE Transactions on Knowledge and Data EngineeringFangzhi Xu, Qika Lin, Jiawei Han, et al.2023 · 141 citations
22. R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement LearningarXiv:2503.05592Huatong Song, Jinhao Jiang, Yingqian Min, et al.2025 · 137 citations
23. From Persona to Personalization: A Survey on Role-Playing Language AgentsarXiv:2404.18231Jiangjie Chen, Xintao Wang, Rui Xu, et al.2024 · 114 citations
24. R-Judge: Benchmarking Safety Risk Awareness for LLM AgentsFindings of the Association for Computational LinguisticsTongxin Yuan, Zhiwei He, Lingzhong Dong, et al.2024 · 97 citations
25. LogicBench: Towards Systematic Evaluation of Logical Reasoning Ability of Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Mihir Parmar, Nisarg Patel, Neeraj Varshney, et al.2024 · 92 citations
26. Diagnosing the First-Order Logical Reasoning Ability Through LogicNLIConference on Empirical Methods in Natural Language Processing (EMNLP)Jidong Tian, Yitian Li, Wenqing Chen, et al.2021 · 86 citations
27. LLaMA-MoE: Building Mixture-of-Experts from LLaMA with Continual Pre-TrainingConference on Empirical Methods in Natural Language Processing (EMNLP)Tong Zhu, Xiaoye Qu, Daize Dong, et al.2024 · 85 citations
28. Testing the General Deductive Reasoning Capacity of Large Language Models Using OOD ExamplesConference on Neural Information Processing Systems (NeurIPS)Abulhair Saparov, Richard Yuanzhe Pang, Vishakh Padmakumar, et al.2023 · 82 citations
29. Self-Reflection in LLM Agents: Effects on Problem-Solving PerformancearXiv:2405.06682 · 2nd International Conference on Foundation and Large Language Models (FLLM 2024), pp. 476-483Matthew Renze, Erhan Guven2024 · 75 citations
30. Apertus: Democratizing Open and Compliant LLMs for Global Language EnvironmentsAnnual Meeting of the Association for Computational Linguistics (ACL)Alejandro Hernández-Cano, Alexander Hägele, Allen Hao Huang, et al.2026 · 67 citations
31. BIDER: Bridging Knowledge Inconsistency for Efficient Retrieval-Augmented LLMs via Key Supporting EvidenceFindings of the Association for Computational LinguisticsJiajie Jin, Yutao Zhu, Yujia Zhou, et al.2024 · 28 citations
32. HPLT 3.0: Very Large-Scale Multilingual Resources for LLMs and MT. Mono- and Bi-lingual Data, Multilingual Evaluation, and Pre-Trained ModelsLanguage Resources and Evaluation Conference (LREC)Stephan Oepen, Nikolay Arefyev, Mikko Aulamo, et al.2026 · 1 citation
33. LCHAIM - Investigating Long Context Reasoning in HebrewEhud Malul, Oriel Perets, Ziv Mor, et al.2025 · 1 citation
34. AYN: A Tiny Yet Competitive Indian Legal Language Model Pretrained from ScratchLanguage Resources and Evaluation Conference (LREC)Mitodru Niyogi, Eric Gaussier, Arnab Bhattacharya2026
35. ThinkStruct: RST-Aware Attention for Logical Reasoning in Machine Reading ComprehensionConference on Computational Natural Language Learning (CoNLL)Nhi Thao Tran, Tien Le, Toan Pham, et al.2026

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