Author

Meng Jiang

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#artificial intelligence Preprint Sep 2026

Learning from Runtime Feedback through Failure-Bank Self-Evolution for Vision-Language-Action Models

Vision-language-action (VLA) models generalize broadly across robotic manipulation tasks, but complex environments require balancing task success with unintended contact. Runtime shields can correct individual actions, but they leave the underlying policy unchanged, so repeated disagreements may create a persistent pol...

M.-Y. Cui, Zhe-Yuan Liu, Yi-Han Zhu et al. · 0 citations

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

Preprint Aug 2026

Knowledge-Verified Emergent Deception in LLM Agents Under Conflicting Incentives

A knowledge-verified benchmark that first confirms through a neutral probe that an agent knows a user's entitlement, and then evaluates whether it makes false claims once an incentive to deny that entitlement is introduced, which reduces the confound between lying and not knowing and enables more rigorous auditing and...

Zhe-Yuan Liu, Wei-Liang Zhao, Xiangchi Yuan et al. · 1 citation