collaborators

6 papers

cs.CV2026

4DPChat: Towards Dynamic Point Cloud Understanding with Failure-Aware Bootstrapping

Xindan Zhang, Weilong Yan, Yufei Shi +5

Point clouds provide a compact and expressive representation of 3D objects, and have recently been integrated into multimodal large language models (MLLMs). However, existing metho…

cs.CV2026

Mind Your Margin and Boundary: Are Your Distilled Datasets Truly Robust?

Muquan Li, Yingyi Ma, Yihong Huang +5

Dataset distillation (DD) compresses a large training set into a small synthetic set for efficient training, but most DD methods optimize only clean accuracy and leave robustness u…

cs.CV2026

One Sentence, One Drama: Personalized Short-Form Drama Generation via Multi-Agent Systems

Yufei Shi, Weilong Yan, Naixuan Huang +5

Existing approaches for digital short-drama production typically rely on one-shot LLM generated scripts and loosely coupled pipelines, which fail to satisfy three key requirements…

cs.AI2026

Risk Awareness Injection: Calibrating Vision-Language Models for Safety without Compromising Utility

Mengxuan Wang, Yuxin Chen, Gang Xu +3

Vision language models (VLMs) extend the reasoning capabilities of large language models (LLMs) to cross-modal settings, yet remain highly vulnerable to multimodal jailbreak attack…

cs.AI2026

When Agents See Humans as the Outgroup: Belief-Dependent Bias in LLM-Powered Agents

Zongwei Wang, Bincheng Gu, Hongyu Yu +5

This paper reveals that LLM-powered agents exhibit not only demographic bias (e.g., gender, religion) but also intergroup bias under minimal "us" versus "them" cues. When such grou…

cs.CV2025

SciEducator: Scientific Video Understanding and Educating via Deming-Cycle Multi-Agent System

Zhiyu Xu, Weilong Yan, Yufei Shi +5

Recent advancements in multimodal large language models (MLLMs) and video agent systems have significantly improved general video understanding. However, when applied to scientific…