3 papers
cs.CL2026
TRE: Encouraging Exploration in the Trust Region
Chao Huang, Yujing Lu, Quangang Li +8
Entropy regularization is a standard technique in reinforcement learning (RL) to enhance exploration, yet it yields negligible effects or even degrades performance in Large Languag…
cs.CR2025
Safety Alignment Should Be Made More Than Just A Few Attention Heads
Chao Huang, Zefeng Zhang, Juewei Yue +3
Current safety alignment for large language models(LLMs) continues to present vulnerabilities, given that adversarial prompting can effectively bypass their safety measures.Our inv…
cs.IR2024
CDRNP: Cross-Domain Recommendation to Cold-Start Users via Neural Process
Xiaodong Li, Jiawei Sheng, Jiangxia Cao +3
Cross-domain recommendation (CDR) has been proven as a promising way to tackle the user cold-start problem, which aims to make recommendations for users in the target domain by tra…