Author

Baiqi Wu

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Review Open access Aug 2026

A Comparative Survey of Security Risks in AI Systems: From LLMs to AI Agents and Embodied Agents

Rapid AI development across industries raises pressing security and privacy risks. This work presents a unified comparison of large language models, AI agents, and embodied agents, introducing a taxonomy of risks spanning data, models, systems, content, and applications, alongside a catalog of 24 specific threats. We c...

Baiqi Wu, Qing-Ming Li, Chun-Yi Zhou et al. · ACM Computing Surveys · 0 citations

#artificial intelligence Preprint Sep 2026

Learn from Whoever Is Right: Answer-Verified Multi-Teacher Distillation for Multi-Domain LLMs

Multi-Teacher Self-Distillation Policy Optimization is introduced, an on-policy distillation method that unifies several frozen teachers into one student model and lifts the weakest domain of Qwen3-8B by 14.79 points and narrows its domain gap by 74.7%, a better balance than serving one matched teacher per domain.

Xi-Xiang He, Xing-Ming Li, Bai-Qi Wu et al. · 2 citations