4 citations · 5 across the 19 of their papers we have counts for
6 papers · 1 filter
A Behavioural Framework for Predicting and Understanding Loss of Control in Frontier Artificial Intelligence Systems
Yao Huang, Yichi Zhang, Yifan Wang +8
Frontier artificial intelligence (AI) systems are increasingly operating over longer horizons with diminishing human oversight, raising the risk of loss of control: systems acting…
Guideline-Grounded Evidence Accumulation for High-Stakes Agent Verification
Yichi Zhang, Nabeel Seedat, Yinpeng Dong +3
As LLM-powered agents have been used for high-stakes decision-making, such as clinical diagnosis, it becomes critical to develop reliable verification of their decisions to facilit…
Oyster-I: Beyond Refusal -- Constructive Safety Alignment for Responsible Language Models
Ranjie Duan, Jiexi Liu, Xiaojun Jia +27
Large language models (LLMs) typically deploy safety mechanisms to prevent harmful content generation. Most current approaches focus narrowly on risks posed by malicious actors, of…
Towards Safe Reasoning in Large Reasoning Models via Corrective Intervention
Yichi Zhang, Yue Ding, Jingwen Yang +7
Although Large Reasoning Models (LRMs) have progressed in solving complex problems, their chain-of-thought (CoT) reasoning often contains harmful content that can persist even when…
A Survey on Autonomy-Induced Security Risks in Large Model-Based Agents
Hang Su, Jun Luo, Chang Liu +4
Recent advances in large language models (LLMs) have catalyzed the rise of autonomous AI agents capable of perceiving, reasoning, and acting in dynamic, open-ended environments. Th…
RealSafe-R1: Safety-Aligned DeepSeek-R1 without Compromising Reasoning Capability
Yichi Zhang, Zihao Zeng, Dongbai Li +3
Large Reasoning Models (LRMs), such as OpenAI o1 and DeepSeek-R1, have been rapidly progressing and achieving breakthrough performance on complex reasoning tasks such as mathematic…