🧑‍🔬 Who cites Keh-Yih Su

320 citations of their works from 309 papers of our library (of the 149,439 whose bibliographies we read) · 86 with a page here, the most cited first · ← Keh-Yih Su

1. Chain-of-Thought Prompting Elicits Reasoning in Large Language ModelsarXiv:2201.11903Jason Wei, Xuezhi Wang, Dale Schuurmans, et al.2022 · 11,499 citations
2. Training Verifiers to Solve Math Word ProblemsarXiv:2110.14168Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, et al.2021 · 3,796 citations
3. Self-Consistency Improves Chain of Thought Reasoning in Language ModelsarXiv:2203.11171Xuezhi Wang, Jason Wei, Dale Schuurmans, et al.2022 · 3,121 citations
4. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
5. Measuring Mathematical Problem Solving With the MATH DatasetarXiv:2103.03874Dan Hendrycks, Collin Burns, Saurav Kadavath, et al.2021 · 2,395 citations
6. Toolformer: Language Models Can Teach Themselves to Use ToolsConference on Neural Information Processing Systems (NeurIPS)Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, et al.2023 · 2,065 citations
7. 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 · 1,756 citations
8. A Comprehensive Overview of Large Language ModelsACM Transactions on Intelligent Systems and TechnologyHumza Naveed, Asad Ullah Khan, Shi Qiu, et al.2023 · 1,287 citations
9. Are NLP Models really able to Solve Simple Math Word Problems?Arkil Patel, Satwik Bhattamishra, Navin Goyal2021 · 890 citations
10. Towards Reasoning in Large Language Models: A SurveyFindings of the Association for Computational LinguisticsJie Huang, Kevin Chen-Chuan Chang2023 · 780 citations
11. Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model SizesFindings of the Association for Computational LinguisticsCheng-Yu Hsieh, Chun-Liang Li, Chih-kuan Yeh, et al.2023 · 690 citations
12. The Flan Collection: Designing Data and Methods for Effective Instruction TuningarXiv:2301.13688Shayne Longpre, Le Hou, Tu Vu, et al.2023 · 607 citations
13. 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
14. MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based FormalismsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Aida Amini, Saadia Gabriel, Shanchuan Lin, et al.2019 · 507 citations
15. Tool Learning with Foundation ModelsACM Computing SurveysYujia Qin, Shengding Hu, Yankai Lin, et al.2023 · 383 citations
16. Solving math word problems with process- and outcome-based feedbackarXiv:2211.14275Jonathan Uesato, Nate Kushman, Ramana Kumar, et al.2022 · 355 citations
17. Faithful Chain-of-Thought ReasoningInternational Joint Conference on Natural Language Processing (IJCNLP)Qing Lyu, Shreya Havaldar, Adam Stein, et al.2023 · 353 citations
18. UL2: Unifying Language Learning ParadigmsarXiv:2205.05131Yi Tay, Mostafa Dehghani, Vinh Q. Tran, et al.2022 · 347 citations
19. Teaching Small Language Models to ReasonAnnual Meeting of the Association for Computational Linguistics (ACL)Lucie Charlotte Magister, Jonathan Mallinson, Jakub Adamek, et al.2023 · 343 citations
20. A Survey of the State of Explainable AI for Natural Language ProcessingConference of the Asia-Pacific Chapter of the Association for Computational Linguistics (AACL)Marina Danilevsky, Kun Qian, Ranit Aharonov, et al.2020 · 294 citations
21. Large Language Models for Mathematical Reasoning: Progresses and ChallengesConference of the European Chapter of the Association for Computational Linguistics (EACL)Janice Ahn, Rishu Verma, Renze Lou, et al.2024 · 280 citations
22. ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem SolvingarXiv:2309.17452Zhibin Gou, Zhihong Shao, Yeyun Gong, et al.2023 · 225 citations
23. Distilling Reasoning Capabilities into Smaller Language ModelsFindings of the Association for Computational LinguisticsKumar Shridhar, Alessandro Stolfo, Mrinmaya Sachan2023 · 219 citations
24. Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical ReasoningarXiv:2209.14610Pan Lu, Liang Qiu, Kai-Wei Chang, et al.2022 · 219 citations
25. 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 · 217 citations
26. NumGLUE: A Suite of Fundamental yet Challenging Mathematical Reasoning TasksAnnual Meeting of the Association for Computational Linguistics (ACL)Swaroop Mishra, Arindam Mitra, Neeraj Varshney, et al.2022 · 197 citations
27. Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMsarXiv:2412.21187Xingyu Chen, Jiahao Xu, Tian Liang, et al.2024 · 192 citations
28. GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical ReasoningFindings of the Association for Computational LinguisticsJiaqi Chen, Jianheng Tang, Jinghui Qin, et al.2021 · 184 citations
29. Evaluating Large Language Models: A Comprehensive SurveyarXiv:2310.19736Zishan Guo, Renren Jin, Chuang Liu, et al.2023 · 182 citations
30. LILA: A Unified Benchmark for Mathematical ReasoningConference on Empirical Methods in Natural Language Processing (EMNLP)Swaroop Mishra, Matthew Finlayson, Pan Lu, et al.2022 · 179 citations
31. Explanations for CommonsenseQA: New Dataset and ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Shourya Aggarwal, Divyanshu Mandowara, Vishwajeet Agrawal, et al.2021 · 164 citations
32. Reasoning with Language Model Prompting: A SurveyarXiv:2212.09597Shuofei Qiao, Yixin Ou, Ningyu Zhang, et al.2022 · 161 citations
33. TheoremQA: A Theorem-driven Question Answering DatasetConference on Empirical Methods in Natural Language Processing (EMNLP)Wenhu Chen, Ming Yin, Max Ku, et al.2023 · 158 citations
34. ROSCOE: A Suite of Metrics for Scoring Step-by-Step ReasoningarXiv:2212.07919Olga Golovneva, Moya Chen, Spencer Poff, et al.2022 · 155 citations
35. Self-Evaluation Guided Beam Search for ReasoningConference on Neural Information Processing Systems (NeurIPS)Yuxi Xie, Kenji Kawaguchi, Yiran Zhao, et al.2023 · 149 citations
36. Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled DataFindings of the Association for Computational LinguisticsKashun Shum, Shizhe Diao, Tong Zhang2023 · 128 citations
37. Navigate through Enigmatic Labyrinth A Survey of Chain of Thought Reasoning: Advances, Frontiers and FuturearXiv:2309.15402Zheng Chu, Jingchang Chen, Qianglong Chen, et al.2023 · 125 citations
38. A Real-World WebAgent with Planning, Long Context Understanding, and Program SynthesisarXiv:2307.12856Izzeddin Gur, Hiroki Furuta, Austin Huang, et al.2023 · 120 citations
39. Orca-Math: Unlocking the potential of SLMs in Grade School MatharXiv:2402.14830Arindam Mitra, Hamed Khanpour, Corby Rosset, et al.2024 · 111 citations
40. GSM-Plus: A Comprehensive Benchmark for Evaluating the Robustness of LLMs as Mathematical Problem SolversAnnual Meeting of the Association for Computational Linguistics (ACL)Qintong Li, Leyang Cui, Xueliang Zhao, et al.2024 · 108 citations
41. Multi-Step Reasoning with Large Language Models, a SurveyACM Computing SurveysAske Plaat, Annie Wong, Suzan Verberne, et al.2024 · 106 citations
42. Learning to Reason Deductively: Math Word Problem Solving as Complex Relation ExtractionZhanming Jie, Jierui Li, Wei Lu2022 · 102 citations
43. Large language models for education: A survey and outlookWang2024 · 101 citations
44. OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning DatasetConference on Neural Information Processing Systems (NeurIPS)Shubham Toshniwal, Ivan Moshkov, Sean Narenthiran, et al.2024 · 98 citations
45. Advancing LLM Reasoning Generalists with Preference TreesarXiv:2404.02078Lifan Yuan, Ganqu Cui, Hanbin Wang, et al.2024 · 94 citations
46. Automated Design of Agentic SystemsarXiv:2408.08435Shengran Hu, Cong Lu, Jeff Clune2024 · 89 citations
47. Mathematics, word problems, common sense, and artificial intelligencearXiv:2301.09723Ernest Davis2023 · 86 citations
48. Solving Math Word Problems via Cooperative Reasoning induced Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Xinyu Zhu, Junjie Wang, Lin Zhang, et al.2023 · 86 citations
49. Common 7B Language Models Already Possess Strong Math CapabilitiesarXiv:2403.04706Chen Li, Weiqi Wang, Jingcheng Hu, et al.2024 · 79 citations
50. SciCode: A Research Coding Benchmark Curated by ScientistsConference on Neural Information Processing Systems (NeurIPS)Minyang Tian, Luyu Gao, Shizhuo Dylan Zhang, et al.2024 · 75 citations
51. MathBench: Evaluating the Theory and Application Proficiency of LLMs with a Hierarchical Mathematics BenchmarkFindings of the Association for Computational LinguisticsHongwei Liu, Zilong Zheng, Yuxuan Qiao, et al.2024 · 70 citations
52. Mixture-of-Experts Meets Instruction Tuning:A Winning Combination for Large Language ModelsarXiv:2305.14705Sheng Shen, Le Hou, Yanqi Zhou, et al.2023 · 70 citations
53. Contrastive Decoding Improves Reasoning in Large Language ModelsarXiv:2309.09117Sean O'Brien, Mike Lewis2023 · 68 citations
54. ARB: Advanced Reasoning Benchmark for Large Language ModelsarXiv:2307.13692Tomohiro Sawada, Daniel Paleka, Alexander Havrilla, et al.2023 · 66 citations
55. A Causal Framework to Quantify the Robustness of Mathematical Reasoning with Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Alessandro Stolfo, Zhijing Jin, Kumar Shridhar, et al.2023 · 65 citations
56. Learning From Mistakes Makes LLM Better ReasonerarXiv:2310.20689Shengnan An, Zexiong Ma, Zeqi Lin, et al.2023 · 64 citations
57. Rho-1: Not All Tokens Are What You NeedarXiv:2404.07965Zhenghao Lin, Zhibin Gou, Yeyun Gong, et al.2024 · 59 citations
58. SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Yige Xu, Xu Guo, Zhiwei Zeng, et al.2025 · 58 citations
59. A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and BeyondarXiv:2503.21614Xiaoye Qu, Yafu Li, Zhao-Chen Su, et al.2025 · 55 citations
60. Contrastive Chain-of-Thought PromptingarXiv:2311.09277Yew Ken Chia, Guizhen Chen, Luu Anh Tuan, et al.2023 · 45 citations
61. Speculative Knowledge Distillation: Bridging the Teacher-Student Gap Through Interleaved SamplingarXiv:2410.11325Wenda Xu, Rujun Han, Zifeng Wang, et al.2024 · 41 citations
62. Towards Effective and Efficient Continual Pre-training of Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Jie Chen, Zhipeng Chen, Jiapeng Wang, et al.2025 · 29 citations
63. ArMATH: a Dataset for Solving Arabic Math Word ProblemsLanguage Resources and Evaluation Conference (LREC)Reem Alghamdi, Zhenwen Liang, Xiangliang Zhang2022 · 17 citations
64. Interactive Evolution: A Neural-Symbolic Self-Training Framework For Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Fangzhi Xu, Qiushi Sun, Kanzhi Cheng, et al.2025 · 15 citations
65. Efficient Tool Use with Chain-of-Abstraction ReasoningInternational Conference on Computational Linguistics (COLING)Silin Gao, Jane Dwivedi-Yu, Ping Yu, et al.2025 · 13 citations
66. Mixed Distillation Helps Smaller Language Model Better ReasoningarXiv:2312.10730Chenglin Li, Qianglong Chen, Liangyue Li, et al.2023 · 11 citations
67. Implicit Reasoning in Large Language Models: A Comprehensive SurveyarXiv:2509.02350Jindong Li, Yali Fu, Li Fan, et al.2025 · 10 citations
68. Improving Reasoning Capabilities in Small Models through Mixture-of-layers Distillation with Stepwise Attention on Key InformationConference on Empirical Methods in Natural Language Processing (EMNLP)Yao Chen, Jiawei Sheng, Wenyuan Zhang, et al.2025 · 10 citations
69. Leveraging Online Olympiad-Level Math Problems for LLMs Training and Contamination-Resistant EvaluationarXiv:2501.14275Sadegh Mahdavi, Muchen Li, Kaiwen Liu, et al.2025 · 10 citations
70. Expression Syntax Information Bottleneck for Math Word ProblemsInternational ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)Jing Xiong, Chengming Li, Min Yang, et al.2023 · 10 citations
71. Exposing the Achilles' Heel: Evaluating LLMs Ability to Handle Mistakes in Mathematical ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Joykirat Singh, Akshay Nambi, Vibhav Vineet2025 · 8 citations
72. Superficial Self-Improved Reasoners Benefit from Model MergingConference on Empirical Methods in Natural Language Processing (EMNLP)Xiangchi Yuan, Chunhui Zhang, Zheyuan Liu, et al.2025 · 8 citations
73. TL;DR: Too Long, Do Re-weighting for Efficient LLM Reasoning CompressionarXiv:2506.02678Zhong-Zhi Li, Xiao Liang, Zihao Tang, et al.2025 · 8 citations
74. SIaM: Self-Improving Code-Assisted Mathematical Reasoning of Large Language ModelsarXiv:2408.15565Dian Yu, Baolin Peng, Ye Tian, et al.2024 · 8 citations
75. Automatic Measuring of English Language Proficiency using MT Evaluation TechnologyProceedings of the Workshop on eLearning for Computational Linguistics and Computational Linguistics for eLearningKeiji Yasuda, Fumiaki Sugaya, Eiichiro Sumita, et al.2004 · 6 citations
76. Do LLMs Really Need 10+ Thoughts for “Find the Time 1000 Days Later”? Towards Structural Understanding of LLM OverthinkingAnnual Meeting of the Association for Computational Linguistics (ACL)Xinliang Frederick Zhang, Anhad Mohananey, Alexandra Chronopoulou, et al.2026 · 4 citations
77. What Makes a Good Curriculum? Disentangling the Effects of Data Ordering on LLM Mathematical ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Yaning Jia, Chunhui Zhang, Xingjian Diao, et al.2026 · 4 citations
78. Evaluating Numeracy of Language Models as a Natural Language Inference TaskFindings of the Association for Computational LinguisticsRahmad Mahendra, Damiano Spina, Lawrence Cavedon, et al.2025 · 4 citations
79. LightReasoner: Can Small Language Models Teach Large Language Models Reasoning?Annual Meeting of the Association for Computational Linguistics (ACL)Jingyuan Wang, Yankai Chen, Zhonghang Li, et al.2026 · 1 citation
80. Agent-GWO: Collaborative Agents for Dynamic Prompt Optimization in Large Language ModelsFindings of the Association for Computational LinguisticsXudong Wang, Chaoning Zhang, Chenghao Li, et al.2026
81. Breaking Block Boundaries: Anchor-based History-stable Decoding for Diffusion Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Shun Zou, Yong Wang, Zehui Chen, et al.2026
82. FlowHN: Adaptive Token Routing for Efficient Parallel Hybrid NetworksAnnual Meeting of the Association for Computational Linguistics (ACL)Mohammad Mahdi Moradi, Walid Ahmed, Shuangyue Wen, et al.2026
83. From Implicit to Explicit: Token-Efficient Logical Supervision for Mathematical Reasoning in LLMsFindings of the Association for Computational LinguisticsShaojie Wang, Liang Zhang2026
84. GALA: Geometric Data Selection with Strategic Prospecting for Large Language Model Self-trainingFindings of the Association for Computational LinguisticsZhongwei Xie, Ruihao Liao, Zimo Wang, et al.2026
85. PURE: Post-hoc Unlocking and REfinement for Discrete Diffusion DecodingFindings of the Association for Computational LinguisticsYangryeol Park, Kunhui Lee, Hanback Choi, et al.2026
86. PyraMathBench: Evaluating and Improving Mathematical Capability in Large Language ModelsFindings of the Association for Computational LinguisticsZetian Ouyang, Linlin Wang, Gerard de Melo, et al.2026

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