A Single Layer to Explain Them All: Understanding Massive Values in Large Language Models
Zeru Shi · Zhenting Wang · Fan Yang · Qifan Wang · Ruixiang Tang
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Zeru Shi · Zhenting Wang · Fan Yang · Qifan Wang · Ruixiang Tang
Can Jin · Rui Wu · Tong Che · Qixin ZHANG · Hongwu Peng · Jiahui Zhao · Zhenting Wang · Wenqi Wei · Ligong Han · Zhao Zhang · Yuan Cao · Ruixiang Tang · Dimitris N. Metaxas
Ensuring that Large Language Models (LLMs) adhere to safety principles without refusing benign requests remains a significant challenge. While OpenAI introduces deliberative alignment (DA) to enhance the safety of its o-series models through reasoning over detailed “code-like” safety rules, the e...
Tingxu Han · Wei Song · Ziqi Ding · Ziming Li · Chunrong Fang · Yuekang Li · Dongfang Liu · Zhenyu Chen · Zhenting Wang
Large language models (LLMs) increasingly mediate decisions in domains where unfair treatment of demographic groups is unacceptable. Existing work probes when biased outputs appear, but gives little insight into the mechanisms that generate them, leaving existing mitigations largely fragile. In t...