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Contextualized Diverse Reasoning: Enhancing Video Question Answering with Multi-Perspective MLLM Pathways

2026-01-05

Abstract excerpt

Video Question Answering (VideoQA) presents significant challenges, demanding comprehensive understanding of dynamic visual content, object interactions, and complex temporal-causal logic. While Multimodal Large Language Models (MLLMs) offer powerful reasoning capabilities, existing approaches often provide singular, potentially flawed reasoning paths, limiting the robustness and depth of VideoQA models. To addres...

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Literature Corpus work: 97eaacce-50a5-5e2e-b2ad-169c1159f9c5
DOI: 10.20944/preprints202512.2254.v1

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