🔗 Who cites «Trial and Error: Exploration-Based Trajectory Optimization of LLM Agents»

32 papers of our library cite it (of the 149,439 whose bibliographies we read) · 10 with a page here, the most cited first · ← back to «Trial and Error: Exploration-Based Trajectory Optimization of LLM Agents»

1. StepTool: Enhancing Multi-Step Tool Usage in LLMs via Step-Grained Reinforcement LearningACM International Conference on Information and Knowledge Management (CIKM)Yuanqing Yu, Zhefan Wang, Weizhi Ma, et al.2024 · 20 citations
2. Interactive Evolution: A Neural-Symbolic Self-Training Framework For Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Fangzhi Xu, Qiushi Sun, Kanzhi Cheng, et al.2025 · 15 citations
3. CRITICTOOL: Evaluating Self-Critique Capabilities of Large Language Models in Tool-Calling Error ScenariosConference on Empirical Methods in Natural Language Processing (EMNLP)Shiting Huang, Zhen Fang, Zehui Chen, et al.2025 · 12 citations
4. Reinforcement Learning for Self-Improving Agent with Skill LibraryAnnual Meeting of the Association for Computational Linguistics (ACL)Jiongxiao Wang, Qiaojing Yan, Yawei Wang, et al.2026 · 8 citations
5. A Goal Without a Plan Is Just a Wish: Efficient and Effective Global Planner Training for Long-Horizon Agent TasksAnnual Meeting of the Association for Computational Linguistics (ACL)Shuzheng Si, Haozhe Zhao, Kangyang Luo, et al.2026 · 4 citations
6. TROJail: Trajectory-Level Optimization for Multi-Turn Large Language Model Jailbreaks with Process RewardsAnnual Meeting of the Association for Computational Linguistics (ACL)Xiqiao Xiong, Ouxiang Li, Zhuo Liu, et al.2026 · 3 citations
7. Hierarchical Reinforcement Learning with Augmented Step-Level Transitions for LLM AgentsAnnual Meeting of the Association for Computational Linguistics (ACL)Shuai Zhen, Yanhua Yu, Ruopei Guo, et al.2026 · 1 citation
8. SAMem: State-Aware Memory as a Fine-Grained Memory for LLM Agents in Decision-MakingFindings of the Association for Computational LinguisticsTong Wang, Pei Xu, Shiyue Cao, et al.2026
9. Seeing Isn't Believing: Mitigating Belief Inertia via Active Intervention in Embodied AgentsFindings of the Association for Computational LinguisticsHanlin Wang, Chak Tou Leong, Jian Wang, et al.2026
10. The Bitter Lesson of Diffusion Language Models for Agentic Workflows: A Comprehensive Reality CheckAnnual Meeting of the Association for Computational Linguistics (ACL)Qingyu Lu, Liang Ding, Kanjian Zhang, et al.2026

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

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