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MLLMs struggle with video temporal-logical reasoning, showing a substantial performance gap compared to human capabilities, especially as complexity increases.
InterleaveThinker transforms standard image generators into powerful tools for interleaved generation, achieving state-of-the-art performance while enhancing reasoning capabilities.
