Author

Tingfeng Hui

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Jul 2026

OpenSkillRisk: Benchmarking Agent Safety When Using Real-World Risky Third-Party Skills

LLM-based agents leverage third-party skills to extend their capabilities in open-world scenarios. However, third-party skills can introduce extra security vulnerabilities, as seemingly harmless skills can contain latent safety risks that only emerge during actual execution. In this work, we conduct a systematic invest...

Qi-Yuan Liu, Tingfeng Hui, Kun Zhan et al. · arXiv.org · 1 citation · ⚡1

#artificial intelligence Preprint May 2026

UniACE: A Unified Framework for Evaluating LLM Agentic Capabilities

This work presents UniACE, a unified framework for model-centric evaluation under an explicit, common execution condition, and reports agent benchmark outcomes as properties of an explicit evaluation configuration, enabling more interpretable and reproducible cross-benchmark comparisons.

Peng-Yu Zhu, Lijun Li, Yaxing Lyu et al. · 3 citations