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Who cites Qiang Fu

216 citations of their works from 213 papers of our library (of the 149,439 whose bibliographies we read) · 67 with a page here, the most cited first · ← Qiang Fu

  1. 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
  2. WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-InstructarXiv:2308.09583Haipeng Luo, Qingfeng Sun, Can Xu, et al.2023 · 372 citations
  3. MAmmoTH: Building Math Generalist Models through Hybrid Instruction TuningarXiv:2309.05653Xiang Yue, Xingwei Qu, Ge Zhang, et al.2023 · 295 citations
  4. Scaling Relationship on Learning Mathematical Reasoning with Large Language ModelsarXiv:2308.01825Zheng Yuan, Hongyi Yuan, Chengpeng Li, et al.2023 · 261 citations
  5. ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem SolvingarXiv:2309.17452Zhibin Gou, Zhihong Shao, Yeyun Gong, et al.2023 · 225 citations
  6. 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
  7. The Prompt Report: A Systematic Survey of Prompt Engineering TechniquesarXiv:2406.06608Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.2024 · 189 citations
  8. Token-Budget-Aware LLM ReasoningarXiv:2412.18547Tingxu Han, Zhenting Wang, Chunrong Fang, et al.2024 · 136 citations
  9. 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
  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 · 122 citations
  11. V-STaR: Training Verifiers for Self-Taught ReasonersarXiv:2402.06457Arian Hosseini, Xingdi Yuan, Nikolay Malkin, et al.2024 · 114 citations
  12. Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-VerificationarXiv:2308.07921Aojun Zhou, Ke Wang, Zimu Lu, et al.2023 · 110 citations
  13. Better Zero-Shot Reasoning with Role-Play PromptingarXiv:2308.07702Aobo Kong, Shiwan Zhao, Hao Chen, et al.2023 · 109 citations
  14. Multi-Step Reasoning with Large Language Models, a SurveyACM Computing SurveysAske Plaat, Annie Wong, Suzan Verberne, et al.2024 · 106 citations
  15. Personal LLM Agents: Insights and Survey about the Capability, Efficiency and SecurityarXiv:2401.05459Yuanchun Li, Hao Wen, Weijun Wang, et al.2024 · 100 citations
  16. Universal Self-Consistency for Large Language Model GenerationarXiv:2311.17311Xinyun Chen, Renat Aksitov, Uri Alon, et al.2023 · 92 citations
  17. More Agents Is All You NeedarXiv:2402.05120Junyou Li, Qin Zhang, Yangbin Yu, et al.2024 · 85 citations
  18. A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?arXiv:2503.24235Qiyuan Zhang, Fuyuan Lyu, Zexu Sun, et al.2025 · 79 citations
  19. Cumulative Reasoning with Large Language ModelsarXiv:2308.04371Yifan Zhang, Jingqin Yang, Yang Yuan, et al.2023 · 74 citations
  20. Skeleton-of-Thought: Prompting LLMs for Efficient Parallel GenerationarXiv:2307.15337Xuefei Ning, Zinan Lin, Zixuan Zhou, et al.2023 · 72 citations
  21. Scaling Large Language Model-based Multi-Agent CollaborationarXiv:2406.07155Chen Qian, Zihao Xie, YiFei Wang, et al.2024 · 70 citations
  22. Learning From Mistakes Makes LLM Better ReasonerarXiv:2310.20689Shengnan An, Zexiong Ma, Zeqi Lin, et al.2023 · 64 citations
  23. AI Agents That MatterarXiv:2407.01502Sayash Kapoor, Benedikt Stroebl, Zachary S. Siegel, et al.2024 · 55 citations
  24. From Decoding to Meta-Generation: Inference-time Algorithms for Large Language ModelsarXiv:2406.16838Sean Welleck, Amanda Bertsch, Matthew Finlayson, et al.2024 · 51 citations
  25. ARGS: Alignment as Reward-Guided SearcharXiv:2402.01694Maxim Khanov, Jirayu Burapacheep, Yixuan Li2024 · 46 citations
  26. Don't throw away your value model! Generating more preferable text with Value-Guided Monte-Carlo Tree Search decodingarXiv:2309.15028Jiacheng Liu, Andrew Cohen, Ramakanth Pasunuru, et al.2023 · 46 citations
  27. 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
  28. Preference Optimization for Reasoning with Pseudo FeedbackarXiv:2411.16345Fangkai Jiao, Geyang Guo, Xingxing Zhang, et al.2024 · 15 citations
  29. Could Thinking Multilingually Empower LLM Reasoning?arXiv:2504.11833Changjiang Gao, Xu Huang, Wenhao Zhu, et al.2025 · 10 citations

146 more citing papers of our library have no page here yet.

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