---
title: "Who cites Kuan Wang — 298 papers of our library"
description: "298 papers of the Elamur Research library cite the works of Kuan Wang, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/kuan-wang/cited-by/"
---
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# Who cites Kuan Wang

298 citations of their works from 298 papers of our library (of the 149,439 whose bibliographies we read) · 60 with a page here, the most cited first · [← Kuan Wang](https://md.research.elamur.ai/free/en/authors/kuan-wang/)

1. [**ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs arXiv:2307.16789**Yujia Qin, Shihao Liang, Yining Ye, et al.*2023 · 589 citations*](https://md.research.elamur.ai/free/en/papers/qin-2023-toolllm-facilitating-large-language-models/)
2. [**Large Language Models: A Survey arXiv:2402.06196**Shervin Minaee, Tomas Mikolov, Narjes Nikzad, et al.*2024 · 471 citations*](https://md.research.elamur.ai/free/en/papers/minaee-2024-large-language-models-survey/)
3. **[API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMs](https://md.research.elamur.ai/free/en/papers/li-2023-api-bank-comprehensive-benchmark-tool/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Minghao Li, Yingxiu Zhao, Bowen Yu, et al.*2023 · 286 citations*
4. [**Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey arXiv:2403.14608**Zeyu Han, Chao Gao, Jinyang Liu, et al.*2024 · 240 citations*](https://md.research.elamur.ai/free/en/papers/han-2024-parameter-efficient-fine-tuning-large/)
5. [**GAIA: a benchmark for General AI Assistants arXiv:2311.12983**Gregoire Mialon, Clementine Fourrier, Craig Swift, et al.*2023 · 232 citations*](https://md.research.elamur.ai/free/en/papers/mialon-2023-gaia-benchmark-general-ai-assistants/)
6. [**OpenHands: An Open Platform for AI Software Developers as Generalist Agents arXiv:2407.16741**Xingyao Wang, Boxuan Li, Yufan Song, et al.*2024 · 221 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-openhands-open-platform-ai/)
7. **[Tool Learning with Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/qu-2024-tool-learning-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Changle Qu, Sunhao Dai, Xiaochi Wei, et al.*2024 · 195 citations*
8. **[Knowledge Conflicts for LLMs: A Survey](https://md.research.elamur.ai/free/en/papers/xu-2024-knowledge-conflicts-llms-survey/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Rongwu Xu, Zehan Qi, Zhijiang Guo, et al.*2024 · 182 citations*
9. [**Evaluating Large Language Models: A Comprehensive Survey arXiv:2310.19736**Zishan Guo, Renren Jin, Chuang Liu, et al.*2023 · 182 citations*](https://md.research.elamur.ai/free/en/papers/guo-2023-evaluating-large-language-models-comprehensive/)
10. **[BinaryBERT: Pushing the Limit of BERT Quantization](https://md.research.elamur.ai/free/en/papers/bai-2021-binarybert-pushing-limit-bert-quantization/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haoli Bai, Wei Zhang, Lu Hou, et al.*2021 · 166 citations*
11. **[Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2025-80-20-rule-high-entropy/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shenzhi Wang, Le Yu, Chang Gao, et al.*2025 · 152 citations*
12. [**TravelPlanner: A Benchmark for Real-World Planning with Language Agents arXiv:2402.01622**Jian Xie, Kai Zhang, Jiangjie Chen, et al.*2024 · 125 citations*](https://md.research.elamur.ai/free/en/papers/xie-2024-travelplanner-benchmark-real-world-planning/)
13. [**From Persona to Personalization: A Survey on Role-Playing Language Agents arXiv:2404.18231**Jiangjie Chen, Xintao Wang, Rui Xu, et al.*2024 · 115 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-persona-personalization-survey-role-playing/)
14. [**MetaTool Benchmark for Large Language Models: Deciding Whether to Use Tools and Which to Use arXiv:2310.03128**Yue Huang, Jiawen Shi, Yuan Li, et al.*2023 · 81 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-metatool-benchmark-large-language-models/)
15. **[AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding Agents](https://md.research.elamur.ai/free/en/papers/trivedi-2024-appworld-controllable-world-apps-people/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Harsh Trivedi, Tushar Khot, Mareike Hartmann, et al.*2024 · 80 citations*
16. **[TTRL: Test-Time Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/zuo-2025-ttrl-test-time-reinforcement-learning/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuxin Zuo, Kaiyan Zhang, Li Sheng, et al.*2025 · 76 citations*
17. [**Kevin: Multi-Turn RL for Generating CUDA Kernels arXiv 2025**Carlo Baronio, Pietro Marsella, Ben Pan, et al.*2025 · 69 citations*](https://md.research.elamur.ai/free/en/papers/baronio-2025-kevin-multi-turn-rl-generating/)
18. [**Reasoning with Exploration: An Entropy Perspective arXiv:2506.14758**Daixuan Cheng, Shaohan Huang, Xuekai Zhu, et al.*2025 · 63 citations*](https://md.research.elamur.ai/free/en/papers/cheng-2025-reasoning-exploration-entropy-perspective/)
19. **[LegalAgentBench: Evaluating LLM Agents in Legal Domain](https://md.research.elamur.ai/free/en/papers/li-2025-legalagentbench-evaluating-llm-agents-legal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haitao Li, Junjie Chen, Jingli Yang, et al.*2025 · 62 citations*
20. **[Generalizing Verifiable Instruction Following](https://md.research.elamur.ai/free/en/papers/pyatkin-2025-generalizing-verifiable-instruction-following/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Valentina Pyatkin, Saumya Malik, Victoria Graf, et al.*2025 · 59 citations*
21. **[Absolute Zero: Reinforced Self-play Reasoning with Zero Data](https://md.research.elamur.ai/free/en/papers/zhao-2025-absolute-zero-reinforced-self-play/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Andrew Zhao, Yiran Wu, Yang Yue, et al.*2025 · 57 citations*
22. [**Spurious Rewards: Rethinking Training Signals in RLVR arXiv:2506.10947**Rulin Shao, Shuyue Stella Li, Rui Xin, et al.*2025 · 53 citations*](https://md.research.elamur.ai/free/en/papers/shao-2025-spurious-rewards-rethinking-training-signals/)
23. **[ToolEyes: Fine-Grained Evaluation for Tool Learning Capabilities of Large Language Models in Real-world Scenarios](https://md.research.elamur.ai/free/en/papers/ye-2025-tooleyes-fine-grained-evaluation-tool/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Junjie Ye, Guanyu Li, SongYang Gao, et al.*2025 · 35 citations*
24. **[Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement](https://md.research.elamur.ai/free/en/papers/kong-2025-time-mqa-time-series-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yaxuan Kong, Yiyuan Yang, Yoontae Hwang, et al.*2025 · 21 citations*
25. [**MindSearch: Mimicking Human Minds Elicits Deep AI Searcher arXiv:2407.20183**Zehui Chen, Kuikun Liu, Qiuchen Wang, et al.*2024 · 20 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-mindsearch-mimicking-human-minds-elicits/)
26. **[CompassVerifier: A Unified and Robust Verifier for LLMs Evaluation and Outcome Reward](https://md.research.elamur.ai/free/en/papers/liu-2025-compassverifier-unified-robust-verifier-llms/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shudong Liu, Hongwei Liu, Junnan Liu, et al.*2025 · 16 citations*
27. [**Harnessing the Reasoning Economy: A Survey of Efficient Reasoning for Large Language Models arXiv:2503.24377**Rui Wang, Hongru Wang, Boyang Xue, et al.*2025 · 16 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-harnessing-reasoning-economy-survey-efficient/)
28. [**Better to Ask in English: Evaluation of Large Language Models on English, Low-resource and Cross-Lingual Settings arXiv:2410.13153**Krishno Dey, Prerona Tarannum, Md. Arid Hasan, et al.*2024 · 16 citations*](https://md.research.elamur.ai/free/en/papers/dey-2024-better-ask-english-evaluation-large/)
29. **[Unlocking Exploration in RLVR: Uncertainty-aware Advantage Shaping for Deeper Reasoning](https://md.research.elamur.ai/free/en/papers/xie-2026-unlocking-exploration-rlvr-uncertainty-aware/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Can Xie, Ruotong Pan, Xiangyu Wu, et al.*2026 · 15 citations*
30. **[ToolHop: A Query-Driven Benchmark for Evaluating Large Language Models in Multi-Hop Tool Use](https://md.research.elamur.ai/free/en/papers/ye-2025-toolhop-query-driven-benchmark-evaluating/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junjie Ye, Zhengyin Du, Xuesong Yao, et al.*2025 · 15 citations*
31. **[CriticLean: Critic-Guided Reinforcement Learning for Mathematical Formalization](https://md.research.elamur.ai/free/en/papers/peng-2026-criticlean-critic-guided-reinforcement-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhongyuan Peng, Yifan Yao, Kaijing Ma, et al.*2026 · 12 citations*
32. [**Prolonged Reasoning Is Not All You Need: Certainty-Based Adaptive Routing for Efficient LLM/MLLM Reasoning arXiv:2505.15154**Jinghui Lu, Haiyang Yu, Siliang Xu, et al.*2025 · 11 citations*](https://md.research.elamur.ai/free/en/papers/lu-2025-prolonged-reasoning-all-need-certainty/)
33. **[When2Call: When (not) to Call Tools](https://md.research.elamur.ai/free/en/papers/ross-2025-when2call-when-not-call-tools/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Hayley Ross, Ameya Sunil Mahabaleshwarkar, Yoshi Suhara*2025 · 11 citations*
34. **[TemplateRL: Structured Template-Guided Reinforcement Learning for LLM Reasoning](https://md.research.elamur.ai/free/en/papers/wu-2026-templaterl-structured-template-guided-reinforcement/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jinyang Wu, Chonghua Liao, Mingkuan Feng, et al.*2026 · 8 citations*
35. **[Feedback-Driven Tool-Use Improvements in Large Language Models via Automated Build Environments](https://md.research.elamur.ai/free/en/papers/ye-2026-feedback-driven-tool-use-improvements/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Junjie Ye, Changhao Jiang, Zhengyin Du, et al.*2026 · 6 citations*
36. **[RL-PLUS: Countering Capability Boundary Collapse of LLMs in Reinforcement Learning with Hybrid-policy Optimization](https://md.research.elamur.ai/free/en/papers/dong-2026-rl-plus-countering-capability-boundary/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yihong Dong, Xue Jiang, Yongding Tao, et al.*2026 · 6 citations*
37. **[Scaling Behaviors of LLM Reinforcement Learning Post-Training: An Empirical Study in Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/tan-2026-scaling-behaviors-llm-reinforcement-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zelin Tan, Hejia Geng, Xiaohang Yu, et al.*2026 · 6 citations*
38. **[Beyond Majority Voting: Towards Fine-grained and More Reliable Reward Signal for Test-Time Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wang-2026-beyond-majority-voting-fine-grained/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weiqin Wang, Yile Wang, Kehao Chen, et al.*2026 · 4 citations*
39. **[Beyond Accuracy: Unveiling Inefficiency Patterns in Tool-Integrated Reasoning](https://md.research.elamur.ai/free/en/papers/su-2026-beyond-accuracy-unveiling-inefficiency-patterns/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qisheng Su, Shiting Huang, Zhen Fang, et al.*2026 · 2 citations*
40. **[Beyond Outcome Verification: Verifiable Process Reward Models for Structured Reasoning](https://md.research.elamur.ai/free/en/papers/pronesti-2026-beyond-outcome-verification-verifiable-process/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Massimiliano Pronesti, Anya Belz, Yufang Hou*2026 · 2 citations*
41. **[Logit Arithmetic Elicits Long Reasoning Capabilities Without Training](https://md.research.elamur.ai/free/en/papers/zhang-2026-logit-arithmetic-elicits-long-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yunxiang Zhang, Muhammad Khalifa, Lechen Zhang, et al.*2026 · 2 citations*
42. **[What If Consensus Lies? Selective-Complementary Reinforcement Learning at Test Time](https://md.research.elamur.ai/free/en/papers/yan-2026-what-if-consensus-lies-selective/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dong Yan, Jian Liang, Yanbo Wang, et al.*2026 · 2 citations*
43. **[A Survey of Deep Learning for Geometry Problem Solving](https://md.research.elamur.ai/free/en/papers/ma-2026-survey-deep-learning-geometry-problem/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jianzhe Ma, Wenxuan Wang, Qin Jin*2026 · 1 citation*
44. **[Chart-RL: Generalized Chart Comprehension via Reinforcement Learning with Verifiable Rewards](https://md.research.elamur.ai/free/en/papers/zhang-2026-chart-rl-generalized-chart-comprehension/) [Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era](https://md.research.elamur.ai/free/en/venues/surgellm/)**Xin Zhang, Xingyu Li, Rongguang Wang, et al.*2026 · 1 citation*
45. **[Easy Samples Are All You Need: Self-Evolving LLMs via Data-Efficient Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/yu-2026-easy-samples-are-all-you/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhiyin Yu, Bo Zhang, Qibin Hou, et al.*2026 · 1 citation*
46. **[A Survey of Large Language Model-Based Search Agents](https://md.research.elamur.ai/free/en/papers/xi-2026-survey-large-language-model-based/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yunjia Xi, Jianghao Lin, Yongzhao Xiao, et al.*2026*
47. **[A Survey of Reinforcement Learning for Large Language Models under Data Scarcity: Challenges and Solutions](https://md.research.elamur.ai/free/en/papers/yu-2026-survey-reinforcement-learning-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiyin Yu, Yuchen Mou, Juncheng Yan, et al.*2026*
48. **[AT\texttwosuperiorPO: Agentic Turn-based Policy Optimization via Tree Search](https://md.research.elamur.ai/free/en/papers/zong-2026-texttwosuperiorpo-agentic-turn-based-policy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zefang Zong, Dingwei Chen, Yang Li, et al.*2026*
49. **[Data Efficient RLVR via Off-Policy Influence Guidance](https://md.research.elamur.ai/free/en/papers/zhu-2026-data-efficient-rlvr-off-policy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Erle Zhu, Dazhi Jiang, Yuan Wang, et al.*2026*
50. **[Entropy Scheduling in Reinforcement Learning for Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-entropy-scheduling-reinforcement-learning-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xingjin Wang, Howe Tissue, Lu Wang, et al.*2026*
51. **[GOAT: A Training Framework for Goal-Oriented Agent with Tools](https://md.research.elamur.ai/free/en/papers/min-2026-goat-training-framework-goal-oriented/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hyunji Min, Sangwon Jung, Junyoung Sung, et al.*2026*
52. **[Layer-Wise High-Impact Parameter Ratio Optimization in Post-Training Quantization for Large Language Models](https://md.research.elamur.ai/free/en/papers/pham-2026-layer-wise-high-impact-parameter/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Cuong Pham, Anh Dung Hoang, Cuong C. Nguyen, et al.*2026*
53. **[PEC-Home: Interpretation of Progressively Elliptical Commands in Smart Homes](https://md.research.elamur.ai/free/en/papers/shan-2026-pec-home-interpretation-progressively-elliptical/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yingyu Shan, Zeming Liu, Silin Li, et al.*2026*
54. **[Profiling-Free Mixed-Precision Quantization for MoE LLMs via Fuzzy Rule Interpolation](https://md.research.elamur.ai/free/en/papers/qi-2026-profiling-free-mixed-precision-quantization/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Huachen Qi, Ruiyu Zhuo, Bowen Shi, et al.*2026*
55. **[SEA-SafeguardBench: Culturally Grounded Safety Benchmark for Southeast Asian Languages](https://md.research.elamur.ai/free/en/papers/tasawong-2026-sea-safeguardbench-culturally-grounded-safety/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Panuthep Tasawong, Jian Gang Ngui, Alham Fikri Aji, et al.*2026*
56. **[Tandem Training for Language Models](https://md.research.elamur.ai/free/en/papers/west-2026-tandem-training-language-models/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Robert West, Ashton Anderson, Ece Kamar, et al.*2026*
57. **[Training Verifier to Assessing Complex Real-World Tool-Use Trajectories](https://md.research.elamur.ai/free/en/papers/sun-2026-training-verifier-assessing-complex-real/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Linzhuang Sun, Mingyang Chen, Hao Liang, et al.*2026*
58. **[When Users Are Happy but Agents Are Wrong: Multi-Dimensional Evaluation of Tool-Augmented Dialogue](https://md.research.elamur.ai/free/en/papers/shourya-2026-when-users-are-happy-but/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Tanya Shourya, Yingfan Wang, Zhaoyi Joey Hou, et al.*2026*
59. **[WildSci: Advancing Scientific Reasoning from In-the-Wild Literature](https://md.research.elamur.ai/free/en/papers/liu-2026-wildsci-advancing-scientific-reasoning-wild/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tengxiao Liu, Deepak Nathani, Zekun Li, et al.*2026*
60. [**Survey of Tool Use in Large Language Models (大语言模型的工具使用综述) Acta Automatica Sinica (自动化学报)**Yining Zheng (郑逸宁), Zhen Yu (余镇), Bufan Li (李不凡), et al.*2025*](https://md.research.elamur.ai/free/en/papers/zheng-2025-tool-use-large/)

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

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