4 papers
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…
COrAL: Order-Agnostic Language Modeling for Efficient Iterative Refinement
Yuxi Xie, Anirudh Goyal, Xiaobao Wu +5
Iterative refinement has emerged as an effective paradigm for enhancing the capabilities of large language models (LLMs) on complex tasks. However, existing approaches typically im…
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…