1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2026
Residual Stream Analysis of Overfitting And Structural Disruptions
Quan Liu, Han Zhou, Wenquan Wu +2
Ensuring that large language models (LLMs) remain both helpful and harmless poses a significant challenge: fine-tuning on repetitive safety datasets, where unsafe prompts are paire…
cs.CL2024
Alignment-Enhanced Decoding:Defending via Token-Level Adaptive Refining of Probability Distributions
Quan Liu, Zhenhong Zhou, Longzhu He +3
Large language models are susceptible to jailbreak attacks, which can result in the generation of harmful content. While prior defenses mitigate these risks by perturbing or inspec…
cs.CL2024★ 1 cited
Speak Out of Turn: Safety Vulnerability of Large Language Models in Multi-turn Dialogue
Zhenhong Zhou, Jiuyang Xiang, Haopeng Chen +3
Large Language Models (LLMs) have been demonstrated to generate illegal or unethical responses, particularly when subjected to "jailbreak." Research on jailbreak has highlighted th…