MoReVQA: Exploring Modular Reasoning Models for Video Question Answering

arXiv:2404.06511v1 Announce Type: cross
Abstract: This paper addresses the task of video question answering (videoQA) via a decomposed multi-stage, modular reasoning framework. Previous modular methods have shown promise with a single planning stage ungrounded in visual content. However, through a simple and effective baseline, we find that such systems can lead to brittle behavior in practice for challenging videoQA settings. Thus, unlike traditional single-stage planning methods, we propose a multi-stage system consisting of an event parser, a grounding stage, and …

abstract arxiv cs.ai cs.cv cs.lg framework however modular paper planning question question answering reasoning simple stage systems through type via video visual