5 papers · 1 filter
Turning Bias into Bugs: Bandit-Guided Style Manipulation Attacks on LLM Judges
Xianglin Yang, Bryan Hooi, Gelei Deng +2
The known stylistic biases in LLM judges, such as a preference for verbosity or specific sentence structures, present an underexplored security vulnerability. In this work, we intr…
Inverting the Shield: Systematically Generating Safety Tests from Policy Specifications
Xiaoyue Lu, Xianglin Yang, Haijun Liu +4
The widespread integration of Large Language Models (LLMs) necessitates rigorous and systematic safety evaluation. Existing paradigms either rely on constructed benchmarks to asses…
Zombie Agents: Persistent Control of Self-Evolving LLM Agents via Self-Reinforcing Injections
Xianglin Yang, Yufei He, Shuo Ji +2
Self-evolving LLM agents update their internal state across sessions, often by writing and reusing long-term memory. This design improves performance on long-horizon tasks but crea…
LLM-enabled Applications Require System-Level Threat Monitoring
Yedi Zhang, Haoyu Wang, Xianglin Yang +2
LLM-enabled applications are rapidly reshaping the software ecosystem by using large language models as core reasoning components for complex task execution. This paradigm shift, h…
Sparse Layer Sharpness-Aware Minimization for Efficient Fine-Tuning
Yifei Cheng, Xianglin Yang, Guoxia Wang +5
Sharpness-aware minimization (SAM) seeks the minima with a flat loss landscape to improve the generalization performance in machine learning tasks, including fine-tuning. However,…