Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

arXiv:2403.12966v1 Announce Type: new
Abstract: In the realm of vision-language understanding, the proficiency of models in interpreting and reasoning over visual content has become a cornerstone for numerous applications. However, it is challenging for the visual encoder in Large Vision-Language Models (LVLMs) to extract useful features tailored to questions that aid the language model's response. Furthermore, a common practice among existing LVLMs is to utilize lower-resolution images, which restricts the ability for visual recognition. Our work introduces the Chain-of-Spot (CoS) …

arxiv cs.cv interactive language language models reasoning spot type vision vision-language models