3 papers
cs.CV2026
From Evaluation to Defense: Advancing Safety in Video Large Language Models
Yiwei Sun, Peiqi Jiang, Chuanbin Liu +3
While the safety risks of image-based large language models (Image LLMs) have been extensively studied, their video-based counterparts (Video LLMs) remain critically under-examined…
cs.CV2026
Decoupling Perception from Reasoning for Hallucination-Resistant Video Understanding
Bowei Pu, Chuanbin Liu, Yifan Ge +5
Video Large Language Models improve reasoning over complex videos by generating intermediate reasoning text. However, reliable reasoning depends on accurate video perception. In ex…
cs.CV2025
RegionRAG: Region-level Retrieval-Augmented Generation for Visual Document Understanding
Yinglu Li, Zhiying Lu, Zhihang Liu +3
Multi-modal Retrieval-Augmented Generation (RAG) has become a critical method for empowering LLMs by leveraging candidate visual documents. However, current methods consider the en…