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arXiv · 2603.01055

MMCOMET: A Large-Scale Multimodal Commonsense Knowledge Graph for Contextual Reasoning

Eileen Wang·Hiba Arnaout·Dhita Pratama·Shuo Yang·Dangyang Liu·Jie Yang·Josiah Poon·Jeff Pan·Caren Han
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Abstract

We present MMCOMET, the first multimodal commonsense knowledge graph (MMKG) that integrates physical, social, and eventive knowledge. MMCOMET extends the ATOMIC2020 knowledge graph to include a visual dimension, through an efficient image retrieval process, resulting in over 900K multimodal triples. This new resource addresses a major limitation of existing MMKGs in supporting complex reasoning tasks like image captioning and storytelling. Through a standard visual storytelling experiment, we show that our holistic approach enables the generation of richer, coherent, and contextually grounded stories than those produced using text-only knowledge. This resource establishes a new foundation for multimodal commonsense reasoning and narrative generation.

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Eileen Wang, Hiba Arnaout, Dhita Pratama, Shuo Yang, Dangyang Liu, Jie Yang, Josiah Poon, Jeff Pan, Caren Han. 2026-03-01. MMCOMET: A Large-Scale Multimodal Commonsense Knowledge Graph for Contextual Reasoning. https://arxiv.org/abs/2603.01055

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