collaborators

5 papers

cs.MA2026

When Truth Is Distributed: Misinformation Derails Collective Fact Recovery in LLM-Based Multi-Agent Systems

Chenfei Yan, Zeyang Yue, Feifei Zhao +6

LLM-based multi-agent systems promise effective collaborative reasoning, but communication may amplify local errors into collective risks, and while existing evaluations emphasize…

cs.AI2026

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…

cs.AI2026

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…

cs.AI2026

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…

cs.NE2025

STEP: A Unified Spiking Transformer Evaluation Platform for Fair and Reproducible Benchmarking

Sicheng Shen, Dongcheng Zhao, Linghao Feng +5

Spiking Transformers have recently emerged as promising architectures for combining the efficiency of spiking neural networks with the representational power of self-attention. How…