1 citations · 2 across the 15 of their papers we have counts for
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QuadSentinel: Sequent Safety for Machine-Checkable Control in Multi-agent Systems
Yiliu Yang, Yilei Jiang, Qunzhong Wang +5
Safety risks arise as large language model-based agents solve complex tasks with tools, multi-step plans, and inter-agent messages. However, deployer-written policies in natural la…
PGPO: Enhancing Agent Reasoning via Pseudocode-style Planning Guided Preference Optimization
Zouying Cao, Runze Wang, Yifei Yang +4
Large Language Model (LLM) agents have demonstrated impressive capabilities in handling complex interactive problems. Existing LLM agents mainly generate natural language plans to…
Beyond Safe Answers: A Benchmark for Evaluating True Risk Awareness in Large Reasoning Models
Baihui Zheng, Boren Zheng, Kerui Cao +9
Despite the remarkable proficiency of \textit{Large Reasoning Models} (LRMs) in handling complex reasoning tasks, their reliability in safety-critical scenarios remains uncertain.…
Equilibrate RLHF: Towards Balancing Helpfulness-Safety Trade-off in Large Language Models
Yingshui Tan, Yilei Jiang, Yanshi Li +6
Fine-tuning large language models (LLMs) based on human preferences, commonly achieved through reinforcement learning from human feedback (RLHF), has been effective in improving th…