collaborators

5 papers

cs.CV2026

Do Multimodal Agents Really Benefit from Tool Use? A Systematic Study of Capability Gains

Garvin Guo, Donglei Yu, Yu Chen +6

Tool-augmented multimodal agents show strong benchmark gains, often taken as evidence that agents have learned to use tools. We argue that this interpretation can be premature: a t…

cs.CL2026

Do Gender Cues Affect LLM Value Trade-offs? Evidence from a Controlled Decision Benchmark

Yangyang Liu, Dong Yu, Pengyuan Liu

Large language models are increasingly used in value-sensitive decision settings, where irrelevant demographic cues should not alter judgments. We construct the Realistic Value Dec…

cs.CL2026

THRD: A Training-Free Multi-Turn Defense Framework for Jailbreak Attacks on Large Language Models

Zhiqing Ma, Zhonghao Xu, Dong Yu +3

Multi-turn jailbreak attacks pose a growing threat to LLMs by exploiting conversational dynamics such as gradual escalation and cross-turn coordination. Existing defenses either re…

cs.CL2026

SPAGBias: Uncovering and Tracing Structured Spatial Gender Bias in Large Language Models

Binxian Su, Haoye Lou, Shucheng Zhu +4

Large language models (LLMs) are being increasingly used in urban planning, but since gendered space theory highlights how gender hierarchies are embedded in spatial organization,…

cs.HC2025

Simulating Human Behavior with the Psychological-mechanism Agent: Integrating Feeling, Thought, and Action

Qing Dong, Pengyuan Liu, Dong Yu +1

Generative agents have made significant progress in simulating human behavior, but existing frameworks often simplify emotional modeling and focus primarily on specific tasks, limi…