4 papers
Ecdysis: Efficient and Effective Training of Runtime Harnesses for LLM Agents
Ruiqing Yue, Yu Cui, Zhuoyu Sun +11
Self-evolving runtime harnesses can substantially improve the capabilities of large language model (LLM) agents and provide a promising paradigm for optimizing agent execution. Exi…
Refusal is Not Safety! Benchmarking Latent Safety Risks of LLM-Driven Content Humorization
Yu Cui, Ruiqing Yue, Tingyu Li +6
Safety defenses for large language models (LLMs) have been extensively studied, with existing approaches focusing on attack detection and refusal mechanisms. Such fixed-form direct…
Spore: Efficient and Training-Free Privacy Extraction Attack on LLMs via Inference-Time Hybrid Probing
Yu Cui, Ruiqing Yue, Hang Fu +6
With the wide adoption of personal AI assistants such as OpenClaw, privacy leakage in user interaction contexts with large language model (LLM) agents has become a critical issue.…
Towards Provably Secure Generative AI: Reliable Consensus Sampling
Yu Cui, Hang Fu, Sicheng Pan +9
Existing research on generative AI security is primarily driven by mutually reinforcing attack and defense methodologies grounded in empirical experience. This dynamic frequently g…