1 citations · 1 across the 12 of their papers we have counts for
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Representational alignment yields generalizable safety in language models
Lingyu Li, Yan Teng, Yingchun Wang +1
Aligning large language models (LLMs) is essential for their safe deployment. Current alignment methods mainly optimize observable responses, yet models remain vulnerable when the…
Mechanistic Origin of Moral Indifference in Language Models
Lingyu Li, Yan Teng, Yingchun Wang
Existing behavioral alignment techniques for Large Language Models (LLMs) often neglect the discrepancy between surface compliance and internal unaligned representations, leaving L…
LinguaSafe: A Comprehensive Multilingual Safety Benchmark for Large Language Models
Zhiyuan Ning, Tianle Gu, Jiaxin Song +8
The widespread adoption and increasing prominence of large language models (LLMs) in global technologies necessitate a rigorous focus on ensuring their safety across a diverse rang…
ESC-Eval: Evaluating Emotion Support Conversations in Large Language Models
Haiquan Zhao, Lingyu Li, Shisong Chen +11
Emotion Support Conversation (ESC) is a crucial application, which aims to reduce human stress, offer emotional guidance, and ultimately enhance human mental and physical well-bein…