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The University of Tokyo
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Query-driven extraction reveals that existing Vision-Language Models falter in multimodal tasks, but a collaborative framework can bridge the performance gap.
Cracking ancient languages like Oracle Bone Script just got easier: a new agent-driven Vision-Language Model leverages the compositional structure of characters to automate reasoning and improve interpretation accuracy.
