HYDRA: A Hyper Agent for Dynamic Compositional Visual Reasoning

arXiv:2403.12884v1 Announce Type: new
Abstract: Recent advances in visual reasoning (VR), particularly with the aid of Large Vision-Language Models (VLMs), show promise but require access to large-scale datasets and face challenges such as high computational costs and limited generalization capabilities. Compositional visual reasoning approaches have emerged as effective strategies; however, they heavily rely on the commonsense knowledge encoded in Large Language Models (LLMs) to perform planning, reasoning, or both, without considering the effect of their decisions on the visual reasoning …

abstract advances agent arxiv capabilities challenges computational costs cs.cv datasets dynamic face however hydra language language models reasoning scale show strategies type vision vision-language models visual vlms