---
title: "Who cites ToolRL: Reward is All Tool — 91 citing papers"
description: "91 papers of the Elamur Research library cite «ToolRL: Reward is All Tool Learning Needs», found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/papers/qian-2025-toolrl-reward-all-tool-learning/cited-by/"
---
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# Who cites «ToolRL: Reward is All Tool Learning Needs»

91 papers of our library cite it (of the 149,439 whose bibliographies we read) · 40 with a page here, the most cited first · [← back to «ToolRL: Reward is All Tool Learning Needs»](https://md.research.elamur.ai/free/en/papers/qian-2025-toolrl-reward-all-tool-learning/)

1. **[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*
2. **[Group-in-Group Policy Optimization for LLM Agent Training](https://md.research.elamur.ai/free/en/papers/feng-2025-group-group-policy-optimization-llm/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Lang Feng, Zhenghai Xue, Tingcong Liu, et al.*2025 · 69 citations*
3. **[WebDancer: Towards Autonomous Information Seeking Agency](https://md.research.elamur.ai/free/en/papers/wu-2025-webdancer-towards-autonomous-information-seeking/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jialong Wu, Baixuan Li, Runnan Fang, et al.*2025 · 50 citations*
4. **[Memory-R1: Enhancing Large Language Model Agents to Manage and Utilize Memories via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/yan-2026-memory-r1-enhancing-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sikuan Yan, Xiufeng Yang, Zuchao Huang, et al.*2026 · 49 citations*
5. **[Search and Refine During Think: Facilitating Knowledge Refinement for Improved Retrieval-Augmented Reasoning](https://md.research.elamur.ai/free/en/papers/shi-2025-search-refine-during-think-facilitating/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yaorui Shi, Sihang Li, Chang Wu, et al.*2025 · 18 citations*
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. [**Distilling LLM Agent into Small Models with Retrieval and Code Tools arXiv:2505.17612**Minki Kang, Jongwon Jeong, Seanie Lee, et al.*2025 · 11 citations*](https://md.research.elamur.ai/free/en/papers/kang-2025-distilling-llm-agent-small-models/)
8. **[TSPO: Breaking the Double Homogenization Dilemma in Multi-turn Search Policy Optimization](https://md.research.elamur.ai/free/en/papers/ma-2026-tspo-breaking-double-homogenization-dilemma/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shichao Ma, Zhiyuan Ma, Ming Yang, et al.*2026 · 7 citations*
9. **[Agentic Memory: Learning Unified Long-Term and Short-Term Memory Management for Large Language Model Agents](https://md.research.elamur.ai/free/en/papers/yu-2026-agentic-memory-learning-unified-long/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yi Yu, Liuyi Yao, Yuexiang Xie, et al.*2026 · 6 citations*
10. **[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*
11. **[EVOTOOL: Self-Evolving Tool-Use Policy Optimization in LLM Agents via Blame-Aware Mutation and Diversity-Aware Selection](https://md.research.elamur.ai/free/en/papers/yang-2026-evotool-self-evolving-tool-use/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shuo Yang, Caren Han, Xueqi Ma, et al.*2026 · 6 citations*
12. **[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*
13. **[LoopTool: Closing the Data–Training Loop for Robust LLM Tool Calls](https://md.research.elamur.ai/free/en/papers/zhang-2026-looptool-closing-data-training-loop/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kangning Zhang, Weiwen Liu, Wenxiang Jiao, et al.*2026 · 6 citations*
14. [**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/)
15. **[OctoTools: A Multi-Agent Framework with Extensible Tools for Complex Reasoning](https://md.research.elamur.ai/free/en/papers/lu-2026-octotools-multi-agent-framework-extensible/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pan Lu, Bowen Chen, Sheng Liu, et al.*2026 · 5 citations*
16. **[ToolScope: Enhancing LLM Agent Tool Use through Tool Merging and Context-Aware Filtering](https://md.research.elamur.ai/free/en/papers/liu-2026-toolscope-enhancing-llm-agent-tool/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Marianne Menglin Liu, Daniel Garcia, Fjona Parllaku, et al.*2026 · 4 citations*
17. **[Behavior Knowledge Merge in Reinforced Agentic Models](https://md.research.elamur.ai/free/en/papers/yuan-2026-behavior-knowledge-merge-reinforced-agentic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiangchi Yuan, Dachuan Shi, Chunhui Zhang, et al.*2026 · 3 citations*
18. **[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*
19. **[The Reasoning Trap: How Enhancing LLM Reasoning Amplifies Tool Hallucination](https://md.research.elamur.ai/free/en/papers/yin-2026-reasoning-trap-how-enhancing-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chenlong Yin, Zeyang Sha, Shiwen Cui, et al.*2026 · 3 citations*
20. **[ToolGate: Contract-Grounded and Verified Tool Execution for LLMs](https://md.research.elamur.ai/free/en/papers/liu-2026-toolgate-contract-grounded-verified-tool/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yanming Liu, Xinyue Peng, Jiannan Cao, et al.*2026 · 3 citations*
21. **[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*
22. **[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*
23. **[ComfyUI-R1: Exploring Reasoning Models for Workflow Generation](https://md.research.elamur.ai/free/en/papers/xu-2026-comfyui-r1-exploring-reasoning-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhenran Xu, Yiyu Wang, Xue Yang, et al.*2026 · 1 citation*
24. **[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*
25. **[MemoBrain: Executive Memory as an Agentic Brain for Reasoning](https://md.research.elamur.ai/free/en/papers/qian-2026-memobrain-executive-memory-as-agentic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hongjin Qian, Zhao Cao, Zheng Liu*2026 · 1 citation*
26. **[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*
27. **[TInR: Exploring Tool-Internalized Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/xu-2026-tinr-exploring-tool-internalized-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qiancheng Xu, Yongqi Li, Fan Liu, et al.*2026 · 1 citation*
28. **[AutoSearch: Adaptive Search Depth for Efficient Agentic RAG via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/sun-2026-autosearch-adaptive-search-depth-efficient/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jingbo Sun, Wenyue Chong, Songjun Tu, et al.*2026*
29. **[Beyond Static Toolsets: Self-Evolving LLM Tool Agents via Continual Documentation Adaptation](https://md.research.elamur.ai/free/en/papers/wu-2026-beyond-static-toolsets-self-evolving/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Bin Wu, Edgar Meij, Emine Yilmaz*2026*
30. **[Beyond the Context Window: Scaling Agentic RL via End-to-end Optimized Context Compression](https://md.research.elamur.ai/free/en/papers/lu-2026-beyond-context-window-scaling-agentic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Miao Lu, Weiwei Sun, Weihua Du, et al.*2026*
31. **[Complex-IF and Beyond: Expert Rubrics for RLVR](https://md.research.elamur.ai/free/en/papers/mehta-2026-complex-if-beyond-expert-rubrics/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Sushant Mehta, Liudas Panavas, Eleanor Fleming, et al.*2026*
32. **[Consolidation or Adaptation? PRISM: Disentangling SFT and RL Data via Gradient Concentration](https://md.research.elamur.ai/free/en/papers/zhao-2026-consolidation-or-adaptation-prism-disentangling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yang Zhao, Yangou Ouyang, Xiao Ding, et al.*2026*
33. **[FeedTrans: Enhance Machine Translation via Feedback](https://md.research.elamur.ai/free/en/papers/sun-2026-feedtrans-enhance-machine-translation-feedback/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Zengkui Sun, Jiali Zeng, Jiaan Wang, et al.*2026*
34. **[GenesisFunc: Multi-Agent Data Generation for Accurate and Generalizable Function-Calling](https://md.research.elamur.ai/free/en/papers/xu-2026-genesisfunc-multi-agent-data-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao-Xiang Xu, Chong Deng, Jiaqing Liu, et al.*2026*
35. **[KARL: Reinforcement Learning for LLM Agents on Multi-Turn Knowledge-Intensive Agentic Tasks](https://md.research.elamur.ai/free/en/papers/sun-2026-karl-reinforcement-learning-llm-agents/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xueqiao Sun, Xiao Liu, Bowen Lv, et al.*2026*
36. **[Knowledge is Not Enough: Injecting RL Skills for Continual Adaptation](https://md.research.elamur.ai/free/en/papers/tang-2026-knowledge-is-not-enough-injecting/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pingzhi Tang, Yiding Wang, Muhan Zhang*2026*
37. **[PARIF: Pushing the Pareto Frontier of Instruction Following and Reasoning with Curriculum Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/mu-2026-parif-pushing-pareto-frontier-instruction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rongchuan Mu, Zexin Wang, Qianyu Wang, et al.*2026*
38. **[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*
39. **[Tailored Primitive Initialization is the Secret Key to Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/yao-2026-tailored-primitive-initialization-is-secret/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yihang Yao, Guangtao Zeng, Raina Wu, et al.*2026*
40. **[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*

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

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