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Who cites Matthew Finlayson

441 citations of their works from 431 papers of our library (of the 149,439 whose bibliographies we read) · 113 with a page here, the most cited first · page 1 of 2 · 1–100 · ← Matthew Finlayson

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  1. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
  2. DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language ModelsarXiv:2402.03300Zhihong Shao, Peiyi Wang, Qihao Zhu, et al.2024 · 2,115 citations
  3. s1: Simple test-time scalingConference on Empirical Methods in Natural Language Processing (EMNLP)Niklas Muennighoff, Zitong Yang, Weijia Shi, et al.2025 · 608 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 Can Be Easily Distracted by Irrelevant ContextarXiv:2302.00093Freda Shi, Xinyun Chen, Kanishka Misra, et al.2023 · 534 citations
  6. MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual ContextsarXiv:2310.02255Pan Lu, Hritik Bansal, Tony Xia, et al.2023 · 468 citations
  7. Tool Learning with Foundation ModelsACM Computing SurveysYujia Qin, Shengding Hu, Yankai Lin, et al.2023 · 383 citations
  8. Augmented Language Models: a SurveyarXiv:2302.07842Grégoire Mialon, Roberto Dessì, Maria Lomeli, et al.2023 · 369 citations
  9. Multimodal Chain-of-Thought Reasoning in Language ModelsarXiv:2302.00923Zhuosheng Zhang, Aston Zhang, Mu Li, et al.2023 · 308 citations
  10. MAmmoTH: Building Math Generalist Models through Hybrid Instruction TuningarXiv:2309.05653Xiang Yue, Xingwei Qu, Ge Zhang, et al.2023 · 295 citations
  11. Large Language Model based Multi-Agents: A Survey of Progress and ChallengesarXiv:2402.01680Taicheng Guo, Xiuying Chen, Yaqi Wang, et al.2024 · 288 citations
  12. DSPy: Compiling Declarative Language Model Calls into Self-Improving PipelinesarXiv:2310.03714Omar Khattab, Arnav Singhvi, Paridhi Maheshwari, et al.2023 · 285 citations
  13. FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving PerformancearXiv:2305.05176Lingjiao Chen, Matei Zaharia, James Zou2023 · 241 citations
  14. ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem SolvingarXiv:2309.17452Zhibin Gou, Zhihong Shao, Yeyun Gong, et al.2023 · 225 citations
  15. Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLParXiv:2212.14024Omar Khattab, Keshav Santhanam, Xiang Lisa Li, et al.2022 · 222 citations
  16. Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical ReasoningarXiv:2209.14610Pan Lu, Liang Qiu, Kai-Wei Chang, et al.2022 · 219 citations
  17. The Prompt Report: A Systematic Survey of Prompt Engineering TechniquesarXiv:2406.06608Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.2024 · 189 citations
  18. Generating Sequences by Learning to Self-CorrectarXiv:2211.00053Sean Welleck, Ximing Lu, Peter West, et al.2022 · 172 citations
  19. Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-SpecificityarXiv:2310.07521Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.2023 · 171 citations
  20. From System 1 to System 2: A Survey of Reasoning Large Language ModelsarXiv:2502.17419Zhong-Zhi Li, Duzhen Zhang, Ming-Liang Zhang, et al.2025 · 165 citations
  21. Orca 2: Teaching Small Language Models How to ReasonarXiv:2311.11045Arindam Mitra, Luciano Del Corro, Shweti Mahajan, et al.2023 · 162 citations
  22. Reasoning with Language Model Prompting: A SurveyarXiv:2212.09597Shuofei Qiao, Yixin Ou, Ningyu Zhang, et al.2022 · 161 citations
  23. Can GPT-3 Perform Statutory Reasoning?arXiv:2302.06100Andrew Blair-Stanek, Nils Holzenberger, Benjamin Van Durme2023 · 154 citations
  24. SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language ModelsarXiv:2307.10635Xiaoxuan Wang, Ziniu Hu, Pan Lu, et al.2023 · 149 citations
  25. A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence GenerationarXiv:2307.03987Neeraj Varshney; Wenlin Yao; Hongming Zhang; Jianshu Chen;, Dong Yu2023 · 143 citations
  26. To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoningarXiv:2409.12183Zayne Sprague, Fangcong Yin, Juan Diego Rodriguez, et al.2024 · 138 citations
  27. OpenWebMath: An Open Dataset of High-Quality Mathematical Web TextarXiv:2310.06786Keiran Paster, Marco Dos Santos, Zhangir Azerbayev, et al.2023 · 132 citations
  28. L1: Controlling How Long A Reasoning Model Thinks With Reinforcement LearningarXiv:2503.04697Pranjal Aggarwal, Sean Welleck2025 · 125 citations
  29. 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 · 122 citations
  30. Orca-Math: Unlocking the potential of SLMs in Grade School MatharXiv:2402.14830Arindam Mitra, Hamed Khanpour, Corby Rosset, et al.2024 · 111 citations
  31. Mathematics, word problems, common sense, and artificial intelligencearXiv:2301.09723Ernest Davis2023 · 86 citations
  32. Paths-over-Graph: Knowledge Graph Empowered Large Language Model ReasoningarXiv:2410.14211Xingyu Tan, Xiaoyang Wang, Qing Liu, et al.2024 · 80 citations
  33. Exploring the Benefits of Training Expert Language Models over Instruction TuningarXiv:2302.03202Joel Jang, Seungone Kim, Seonghyeon Ye, et al.2023 · 63 citations
  34. Meta-Prompting: Enhancing Language Models with Task-Agnostic ScaffoldingarXiv:2401.12954Mirac Suzgun, Adam Tauman Kalai2024 · 62 citations
  35. MathChat: Converse to Tackle Challenging Math Problems with LLM AgentsarXiv:2306.01337Yiran Wu; Feiran Jia; Shaokun Zhang; Hangyu Li; Erkang Zhu; Yue Wang; Yin Tat Lee; Richard Peng; Qingyun Wu;, Chi Wang2023 · 46 citations
  36. GLoRe: When, Where, and How to Improve LLM Reasoning via Global and Local RefinementsarXiv:2402.10963Alex Havrilla, Sharath Raparthy, Christoforus Nalmpantis, et al.2024 · 45 citations
  37. Through the Lens of Core Competency: Survey on Evaluation of Large Language ModelsarXiv:2308.07902Ziyu Zhuang, Qiguang Chen, Longxuan Ma, et al.2023 · 35 citations
  38. Timo: Towards Better Temporal Reasoning for Language ModelsarXiv:2406.14192Zhaochen Su, Jun Zhang, Tong Zhu, et al.2024 · 19 citations
  39. Evaluating statistical language models as pragmatic reasonersarXiv:2305.01020Benjamin Lipkin, Lionel Wong, Gabriel Grand, et al.2023 · 18 citations
  40. Skills-in-Context Prompting: Unlocking Compositionality in Large Language ModelsarXiv:2308.00304Jiaao Chen, Xiaoman Pan, Dian Yu, et al.2023 · 17 citations
  41. ChemAgent: Self-updating Library in Large Language Models Improves Chemical ReasoningarXiv:2501.06590Xiangru Tang, Tianyu Hu, Muyang Ye, et al.2025 · 15 citations
  42. Data-driven Discovery with Large Generative ModelsarXiv:2402.13610Bodhisattwa Prasad Majumder, Harshit Surana, Dhruv Agarwal, et al.2024 · 15 citations
  43. Aligning Large Language Models with Human Opinions through Persona Selection and Value — Belief — Norm ReasoningarXiv:2311.08385Do Xuan Long, Kenji Kawaguchi, Min-Yen Kan, et al.2023 · 12 citations
  44. Advancing Mathematical Reasoning in Language Models: The Impact of Problem-Solving Data, Data Synthesis Methods, and Training StagesarXiv:2501.14002Zui Chen, Tianqiao Liu, Mi Tian, et al.2025 · 9 citations
  45. CER: Confidence Enhanced Reasoning in LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Ali Razghandi, Seyed Mohammad Hadi Hosseini, Mahdieh Soleymani Baghshah2025 · 8 citations
  46. Cutting Through the Noise: Boosting LLM Performance on Math Word ProblemsUjjwala Anantheswaran, Himanshu Gupta, Kevin Scaria, et al.2024 · 7 citations
  47. PreWoMe: Exploiting Presuppositions as Working Memory for Long Form Question AnsweringWookje Han, Jinsol Park, Kyungjae Lee2023 · 4 citations

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