87 citations · 225 across the 56 of their papers we have counts for
5 papers · 1 filter
Light Alignment Improves LLM Safety via Model Self-Reflection with a Single Neuron
Sicheng Shen, Mingyang Lv, Han Shen +7
The safety of large language models (LLMs) has increasingly emerged as a fundamental aspect of their development. Existing safety alignment for LLMs is predominantly achieved throu…
Efficient LLM Safety Evaluation through Multi-Agent Debate
Dachuan Lin, Guobin Shen, Zihao Yang +3
Safety evaluation of large language models (LLMs) increasingly relies on LLM-as-a-judge pipelines, but strong judges can still be expensive to use at scale. We study whether struct…
Safety Instincts: LLMs Learn to Trust Their Internal Compass for Self-Defense
Guobin Shen, Dongcheng Zhao, Haibo Tong +3
Ensuring Large Language Model (LLM) safety remains challenging due to the absence of universal standards and reliable content validators, making it difficult to obtain effective tr…
Super Co-alignment of Human and AI for Sustainable Symbiotic Society
Yi Zeng, Feifei Zhao, Yuwei Wang +13
As Artificial Intelligence (AI) advances toward Artificial General Intelligence (AGI) and eventually Artificial Superintelligence (ASI), it may potentially surpass human control, d…
Brain-inspired and Self-based Artificial Intelligence
Yi Zeng, Feifei Zhao, Yuxuan Zhao +17
The question "Can machines think?" and the Turing Test to assess whether machines could achieve human-level intelligence is one of the roots of AI. With the philosophical argument…