3 accepted papers
Although current large Vision-Language Models (VLMs) have advanced in multimodal understanding and reasoning, their fundamental perceptual and reasoning abilities remain limited. Specifically, even on simple jigsaw tasks, existing VLMs perform near randomly, revealing deficiencies in core perception…
Large Vision-Language Models (LVLMs) have made significant strides in the field of video understanding in recent times. Nevertheless, existing video benchmarks predominantly rely on text prompts for evaluation, which often require complex referential language and diminish both the accuracy and effic…
High-quality image captions are essential for improving modality alignment and visual understanding in Large Vision-Language Models (LVLMs). However, the scarcity of ultra-detailed image caption data limits further advancements. This paper presents a systematic pipeline for generating high-quality,