3 papers
cs.AI2026
SkillZip: Evaluation-Free Skill Compression for Self-Evolving Agents by Discovering Reusable Structure
Xiaofan Bai, Hongqiang Lin, Chao Liu +4
Self-evolving agents accumulate reusable skills by appending successful procedures and failure fixes. Over time, the same requirement is often restated in several branches, example…
cs.CR2026
Targeted Counterfactual Fingerprinting for Black-Box LLM Ownership Verification
Yutong Wu, Xiaofan Bai, Shixin Li +10
Large language models (LLMs) are high-value assets that can be derived through redeployment, fine-tuning, quantization, or further alignment. Because deployed LLMs are commonly exp…
cs.AI2026
Rethinking Self-Evolution: A Constrained Exploration-Exploitation Process for Mitigating Skill Overfitting
Hongqiang Lin, Chao Liu, Xiaofan Bai +4
The paper introduces SkillBoost, a three-stage framework that reduces overfitting of trainable skills in large language model agents by balancing constrained exploitation of failur…