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cs.CL2026
AutoMonitor-Bench: Evaluating the Reliability of LLM-Based Misbehavior Monitor
Shu Yang, Jingyu Hu, Tong Li +3
We introduce AutoMonitor-Bench, the first benchmark designed to systematically evaluate the reliability of LLM-based misbehavior monitors across diverse tasks and failure modes. Au…
cs.CL2025★ 1 cited
STShield: Single-Token Sentinel for Real-Time Jailbreak Detection in Large Language Models
Xunguang Wang, Wenxuan Wang, Zhenlan Ji +4
Large Language Models (LLMs) have become increasingly vulnerable to jailbreak attacks that circumvent their safety mechanisms. While existing defense methods either suffer from ada…
cs.CL2024★ 1 cited
Testing and Evaluation of Large Language Models: Correctness, Non-Toxicity, and Fairness
Wenxuan Wang
Large language models (LLMs), such as ChatGPT, have rapidly penetrated into people's work and daily lives over the past few years, due to their extraordinary conversational skills…