---
title: "Who cites ReTool: Reinforcement Learning — 85 citing papers"
description: "85 papers of the Elamur Research library cite «ReTool: Reinforcement Learning for Strategic Tool Use in LLMs», found in their bibliographies…"
canonical: "https://research.elamur.ai/free/en/papers/feng-2025-retool-reinforcement-learning-strategic-tool/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/feng-2025-retool-reinforcement-learning-strategic-tool/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [ReTool: Reinforcement Learning for Strategic Tool…](https://md.research.elamur.ai/free/en/papers/feng-2025-retool-reinforcement-learning-strategic-tool/) / cited by

# Who cites «ReTool: Reinforcement Learning for Strategic Tool Use in LLMs»

85 papers of our library cite it (of the 149,439 whose bibliographies we read) · 29 with a page here, the most cited first · [← back to «ReTool: Reinforcement Learning for Strategic Tool Use in LLMs»](https://md.research.elamur.ai/free/en/papers/feng-2025-retool-reinforcement-learning-strategic-tool/)

1. **[Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 176 citations*
2. **[WebThinker: Empowering Large Reasoning Models with Deep Research Capability](https://md.research.elamur.ai/free/en/papers/li-2025-webthinker-empowering-large-reasoning-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xiaoxi Li, Jiajie Jin, Guanting Dong, et al.*2025 · 72 citations*
3. [**UI-TARS-2 Technical Report: Advancing GUI Agent with Multi-Turn Reinforcement Learning arXiv:2509.02544**Haoming Wang, Haoyang Zou, Huatong Song, et al.*2025 · 26 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-ui-tars-2-technical/)
4. **[START: Self-taught Reasoner with Tools](https://md.research.elamur.ai/free/en/papers/li-2025-start-self-taught-reasoner-tools/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chengpeng Li, Mingfeng Xue, Zhenru Zhang, et al.*2025 · 21 citations*
5. [**Seed-Prover 1.5: Mastering Undergraduate-Level Theorem Proving via Learning from Experience arXiv:2512.17260**Jiangjie Chen, Wenxiang Chen, Jiacheng Du, et al.*2025 · 19 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-seed-prover-1-5/)
6. **[VerIF: Verification Engineering for Reinforcement Learning in Instruction Following](https://md.research.elamur.ai/free/en/papers/peng-2025-verif-verification-engineering-reinforcement-learning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hao Peng, Yunjia Qi, Xiaozhi Wang, et al.*2025 · 18 citations*
7. **[ATLAS: Orchestrating Heterogeneous Models and Tools for Multi-Domain Complex Reasoning](https://md.research.elamur.ai/free/en/papers/wu-2026-atlas-orchestrating-heterogeneous-models-tools/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jinyang Wu, Guocheng Zhai, Ruihan Jin, et al.*2026 · 8 citations*
8. **[NOVER: Incentive Training for Language Models via Verifier-Free Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/liu-2025-nover-incentive-training-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wei Liu, Siya Qi, Xinyu Wang, et al.*2025 · 7 citations*
9. **[CriticSearch: Fine-Grained Credit Assignment for Search Agents via a Retrospective Critic](https://md.research.elamur.ai/free/en/papers/zhang-2026-criticsearch-fine-grained-credit-assignment/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yaocheng Zhang, Haohuan Huang, Zijun Song, et al.*2026 · 6 citations*
10. [**rStar2-Agent: Agentic Reasoning Technical Report arXiv:2508.20722**Ning Shang, Yifei Liu, Yi Zhu, et al.*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/shang-2025-rstar2-agent-agentic-reasoning/)
11. **[Mem²Evolve: Towards Self-Evolving Agents via Co-Evolutionary Capability Expansion and Experience Distillation](https://md.research.elamur.ai/free/en/papers/cheng-2026-mem-2-evolve-self-evolving/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zihao Cheng, Zeming Liu, Yingyu Shan, et al.*2026 · 5 citations*
12. **[Learning While Staying Curious: Entropy-Preserving Supervised Fine-Tuning via Adaptive Self-Distillation for Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/wang-2026-learning-while-staying-curious-entropy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Wang, Hao Gu, Hongming Piao, et al.*2026 · 3 citations*
13. **[Lost in Execution: On the Multilingual Robustness of Tool Calling in Large Language Models](https://md.research.elamur.ai/free/en/papers/luo-2026-lost-execution-multilingual-robustness-tool/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zheng Luo, T Pranav Kutralingam, Ogochukwu N. Okoani, et al.*2026 · 3 citations*
14. **[Failure makes the agent stronger: Enhancing Accuracy through Structured Reflection for Reliable Tool Interactions](https://md.research.elamur.ai/free/en/papers/su-2026-failure-makes-agent-stronger-enhancing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Junhao Su, Yuanliang Wan, Junwei Yang, et al.*2026 · 2 citations*
15. **[Timely Machine: Awareness of Time Makes Test-Time Scaling Agentic](https://md.research.elamur.ai/free/en/papers/ma-2026-timely-machine-awareness-time-makes/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yichuan Ma, Linyang Li, Yongkang Chen, et al.*2026 · 2 citations*
16. **[COMPASS: Enhancing Agent Long-Horizon Reasoning with Evolving Context](https://md.research.elamur.ai/free/en/papers/wan-2026-compass-enhancing-agent-long-horizon/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guangya Wan, Mingyang Ling, Xiaoqi Ren, et al.*2026 · 1 citation*
17. **[CoVerRL: Breaking the Consensus Trap in Label-Free Reasoning via Generator-Verifier Co-Evolution](https://md.research.elamur.ai/free/en/papers/pan-2026-coverrl-breaking-consensus-trap-label/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Teng Pan, Yuchen Yan, Zixuan Wang, et al.*2026 · 1 citation*
18. **[MatchTIR: Fine-Grained Supervision for Tool-Integrated Reasoning via Bipartite Matching](https://md.research.elamur.ai/free/en/papers/qu-2026-matchtir-fine-grained-supervision-tool/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Changle Qu, Sunhao Dai, Hengyi Cai, et al.*2026 · 1 citation*
19. **[SepSeq: A Training-Free Framework for Long Numerical Sequence Processing in LLMs](https://md.research.elamur.ai/free/en/papers/sun-2026-sepseq-training-free-framework-long/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jie Sun, Yu Liu, Lu Han, et al.*2026 · 1 citation*
20. **[Adversarial Yet Cooperative: Multi-Perspective Reasoning in Retrieved-Augmented Language Models](https://md.research.elamur.ai/free/en/papers/xu-2026-adversarial-yet-cooperative-multi-perspective/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Can Xu, Lingyong Yan, Jiayi Wu, et al.*2026*
21. **[AgentV-RL: Scaling Reward Modeling with Agentic Verifier](https://md.research.elamur.ai/free/en/papers/zhang-2026-agentv-rl-scaling-reward-modeling/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiazheng Zhang, Ziche Fu, Zhiheng Xi, et al.*2026*
22. **[Aligning Agents via Planning: A Benchmark for Trajectory-Level Reward Modeling](https://md.research.elamur.ai/free/en/papers/wang-2026-aligning-agents-planning-benchmark-trajectory/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiaxuan Wang, Yulan Hu, Wenjin Yang, et al.*2026*
23. **[Mixture-of-Minds: Multi-Agent Reinforcement Learning for Table Understanding](https://md.research.elamur.ai/free/en/papers/zhou-2026-mixture-minds-multi-agent-reinforcement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuhang Zhou, Mingrui Zhang, Ke Li, et al.*2026*
24. **[QFinZero: A Unified Financial Toolchain for LLM-Based Trading Agents](https://md.research.elamur.ai/free/en/papers/luo-2026-qfinzero-unified-financial-toolchain-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haochen Luo, Yifan LI, Ho Tin Ko, et al.*2026*
25. **[ScaleBox: Enabling High-Fidelity and Scalable Code Verification for Large Language Models](https://md.research.elamur.ai/free/en/papers/zheng-2026-scalebox-enabling-high-fidelity-scalable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiasheng Zheng, Xin Zheng, Boxi Cao, et al.*2026*
26. **[SGA-MCTS: Decoupling Planning from Execution via Training-Free Atomic Experience Retrieval](https://md.research.elamur.ai/free/en/papers/xie-2026-sga-mcts-decoupling-planning-execution/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xin Xie, Dongyun Xue, Wuguannan Yao, et al.*2026*
27. **[ToolCPT: Improving Tool Utilization in LLM Agents via Continuous Pre-training](https://md.research.elamur.ai/free/en/papers/yang-2026-toolcpt-improving-tool-utilization-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yifan Yang, Jinghui Lu, Evadeng, et al.*2026*
28. **[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*
29. **[When to Trust Tools? Adaptive Tool Trust Calibration For Tool-Integrated Math Reasoning](https://md.research.elamur.ai/free/en/papers/xu-2026-when-trust-tools-adaptive-tool/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ruotao Xu, Yixin Ji, Yu Luo, et al.*2026*

56 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/feng-2025-retool-reinforcement-learning-strategic-tool/) — ReTool: Reinforcement Learning for Strategic Tool Use in LLMs
