2 citations · 2 across the 11 of their papers we have counts for
4 papers · 1 filter
Can Multimodal Large Language Models Understand OCT?
Baochen Fu, Wenzhi Deng, Baihao Jin +5
Optical coherence tomography (OCT) imaging is essential for the diagnosis and treatment of retinal diseases. Although multimodal large language models (MLLMs) have demonstrated con…
Delineating Knowledge Boundaries for Honest Large Vision-Language Models
Junru Song, Yimeng Hu, Yijing Chen +4
Large Vision-Language Models (VLMs) have achieved remarkable multimodal performance yet remain prone to factual hallucinations, particularly in long-tail or specialized domains. Mo…
VideoAgent: A Memory-augmented Multimodal Agent for Video Understanding
Yue Fan, Xiaojian Ma, Rujie Wu +4
We explore how reconciling several foundation models (large language models and vision-language models) with a novel unified memory mechanism could tackle the challenging video und…
CLOVA: A Closed-Loop Visual Assistant with Tool Usage and Update
Zhi Gao, Yuntao Du, Xintong Zhang +4
Utilizing large language models (LLMs) to compose off-the-shelf visual tools represents a promising avenue of research for developing robust visual assistants capable of addressing…