@inproceedings{yang-etal-2026-evotool,
    title = "{EVOTOOL}: Self-Evolving Tool-Use Policy Optimization in {LLM} Agents via Blame-Aware Mutation and Diversity-Aware Selection",
    author = "Yang, Shuo  and
      Han, Caren  and
      Ma, Xueqi  and
      Li, Yan  and
      Madani, Mohammad Reza Ghasemi  and
      Hovy, Eduard",
    editor = "Liakata, Maria  and
      Moreira, Viviane P.  and
      Zhang, Jiajun  and
      Jurgens, David",
    booktitle = "Proceedings of the 64th Annual Meeting of the {A}ssociation for {C}omputational {L}inguistics (Volume 1: Long Papers)",
    month = jul,
    year = "2026",
    address = "San Diego, California, United States",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl/2026.acl-long.2016/",
    pages = "43553--43572",
    ISBN = "979-8-89176-390-6",
    abstract = "LLM-based agents depend on effective tool-use policies to solve complex tasks, yet optimizing these policies remains challenging dueto delayed supervision and the difficulty ofcredit assignment in long-horizon trajectories.Existing optimization approaches tend to beeither monolithic, which are prone to entangling behaviors, or single-aspect, which ignorecross-module error propagation. To addressthese limitations, we propose EVOTOOL, a self-evolving framework that optimizes a modulartool-use policy via a gradient-free evolutionary paradigm. EVOTOOL decomposes agent{'}stool-use policy into four modules, includingPlanner, Selector, Caller, and Synthesizer, anditeratively improves them through three mechanisms. Trajectory-Grounded Blame Attribution uses diagnostic traces to localize failuresto a specific module. Feedback-Guided Targeted Mutation then edits only that modulevia natural-language critique. Diversity-AwarePopulation Selection preserves complementarycandidates to ensure solution diversity. Acrossfour diverse benchmarks, EVOTOOL outperforms strong baselines by over 5 points on bothGPT-4.1 and Qwen3-8B, while achieving superior efficiency and transferability."
}