AutoVQA-G: Self-Improving Agentic Framework for Automated Visual Question Answering and Grounding Annotation
arXiv:2604.17488v1 Announce Type: new
Abstract: Manual annotation of high-quality visual question answering with grounding (VQA-G) datasets, which pair visual questions with evidential grounding, is crucial for advancing vision-language models (VLMs),…