1 citations · 1 across the 15 of their papers we have counts for
10 papers · 1 filter
MediSkill-Evo: Process-Constrained Self-Evolution for Evidence-Grounded Clinical Interaction
Ruoyu Wu, Shenfu Xie, Yinqian Sun +2
Interactive clinical agents operate under partial observability, so reliable care depends on reaching the correct diagnosis through evidence-grounded, safe interactions. Yet existi…
SciRisk-Bench: A Risk-Dimension-Aware Benchmark for AI4Science Safety
Linghao Feng, Yinqian Sun, Dongqi Liang +8
Large language models (LLMs) are increasingly embedded in AI for Science (AI4Science) workflows, from scientific question answering and literature analysis to laboratory planning a…
CogManip: Benchmarking Manipulative Behavior in Multi-Turn Interactions with Large Language Model
Zeyang Yue, Chenfei Yan, Feifei Zhao +5
Whether Large Language Models (LLMs) exhibit covert psychological manipulation in complex human-AI interactions has garnered increasing safety concerns. However, existing AI safety…
ForesightSafety-SAGE:A Fully Automated Scenario Generation and Safety Evaluation Framework for LLM Agents
Lu Jia, Haibo Tong, Feifei Zhao +5
Large language models (LLMs) are increasingly evolving from simple text-based interaction systems into LLM agents that can maintain memory, use tools, access external environments,…
ForesightSafety Bench: A Frontier Risk Evaluation and Governance Framework towards Safe AI
Haibo Tong, Feifei Zhao, Linghao Feng +18
Rapidly evolving AI exhibits increasingly strong autonomy and goal-directed capabilities, accompanied by derivative systemic risks that are more unpredictable, difficult to control…
CogToM: A Comprehensive Theory of Mind Benchmark inspired by Human Cognition for Large Language Models
Haibo Tong, Zeyang Yue, Feifei Zhao +6
Whether Large Language Models (LLMs) truly possess human-like Theory of Mind (ToM) capabilities has garnered increasing attention. However, existing benchmarks remain largely restr…
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…
Autonomous Alignment with Human Value on Altruism through Considerate Self-imagination and Theory of Mind
Haibo Tong, Enmeng Lu, Yinqian Sun +4
With the widespread application of Artificial Intelligence (AI) in human society, enabling AI to autonomously align with human values has become a pressing issue to ensure its sust…
Building Altruistic and Moral AI Agent with Brain-inspired Emotional Empathy Mechanisms
Feifei Zhao, Hui Feng, Haibo Tong +5
As AI closely interacts with human society, it is crucial to ensure that its behavior is safe, altruistic, and aligned with human ethical and moral values. However, existing resear…