collaborators

5 papers

cs.CL2026

Recognition-Refusal Misalignment in LLMs: Why Models Answer Structurally Unanswerable Questions

Yucheng Du, Xiyang Hu

Large language models often answer structurally unanswerable questions, such as computing cot(-540°) or evaluating (1).startswith("1"), instead of abstaining. We ask whether this f…

cs.CV2026

Do Vision Language Models Understand Human Engagement in Games?

Ziyi Wang, Qizan Guo, Rishitosh Singh +1

Inferring human engagement from gameplay video is important for game design and player-experience research, yet it remains unclear whether vision--language models (VLMs) can infer…

cs.CL2026

Multimodal Generative Engine Optimization: Rank Manipulation for Vision-Language Model Rankers

Yixuan Du, Chenxiao Yu, Haoyan Xu +3

Vision-Language Models (VLMs) integrate visual and textual knowledge into unified representations that increasingly underpin modern retrieval and recommendation systems. However, i…

cs.CL2026

Value-Action Alignment in Large Language Models under Privacy-Prosocial Conflict

Guanyu Chen, Chenxiao Yu, Xiyang Hu

Large language models (LLMs) are increasingly used to simulate decision-making tasks involving personal data sharing, where privacy concerns and prosocial motivations can push choi…

cs.CL2025

Are LLMs Reliable Rankers? Rank Manipulation via Two-Stage Token Optimization

Tiancheng Xing, Jerry Li, Yixuan Du +1

Large language models (LLMs) are increasingly used as rerankers in information retrieval, yet their ranking behavior can be steered by small, natural-sounding prompts. To expose th…