Grounded Multi-Hop VideoQA in Long-Form Egocentric Videos
GeLM Model
We propose a novel architecture, termed as GeLM for MH-VidQA, to leverage the world knowledge reasoning capabilities of multi-modal large language models (LLMs), while incorporating a grounding module to retrieve temporal evidence in the video with flexible grounding tokens.
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