4 papers
Manager: Aggregating Insights from Unimodal Experts in Two-Tower VLMs and MLLMs
Xiao Xu, Libo Qin, Wanxiang Che +1
Two-Tower Vision--Language Models (VLMs) have demonstrated strong performance across various downstream VL tasks. While BridgeTower further enhances performance by building bridges…
Exploring Multi-Grained Concept Annotations for Multimodal Large Language Models
Xiao Xu, Tianhao Niu, Yuxi Xie +3
Multimodal Large Language Models (MLLMs) excel in vision--language tasks by pre-training solely on coarse-grained concept annotations (e.g., image captions). We hypothesize that in…
V-DPO: Mitigating Hallucination in Large Vision Language Models via Vision-Guided Direct Preference Optimization
Yuxi Xie, Guanzhen Li, Xiao Xu +1
Large vision-language models (LVLMs) suffer from hallucination, resulting in misalignment between the output textual response and the input visual content. Recent research indicate…
MVP-Bench: Can Large Vision--Language Models Conduct Multi-level Visual Perception Like Humans?
Guanzhen Li, Yuxi Xie, Min-Yen Kan
Humans perform visual perception at multiple levels, including low-level object recognition and high-level semantic interpretation such as behavior understanding. Subtle difference…