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Author

Zheyuan Liu

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Preprint Aug 2026

Forgotten in Weights, Recovered by Tools: Agentic Tool Unlearning for LLM Agents

Experiments on RWKU and MUSE across different LLM architectures show that ATU achieves a better balance between target forgetting and retained utility, making unlearning more robust under tool-augmented agent deployment.

Baicheng Chen, Zhe-Yuan Liu, Jingyu Zhang et al. · 0 citations
Jul 2026

MemoHarness: Agent Harnesses That Learn from Experience

MemoHarness is introduced, an adaptive harness optimization framework that learns from its own executions and improves over the fixed harnesses it is compared against and shows selective transfer to unseen suites and base models.

Yue Huang, Wenjie Wang, Han Bao et al. · 4 citations

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