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IntReal introduces IntReal-100K, a real-world interleaved multimodal dataset, and a seven-dimension evaluation suite for diagnosing unified multimodal models, showing that modality-specific training can improve interleaved text-image generation.
InterleaveThinker introduces a multi-agent pipeline with planner and critic agents to enable interleaved text-image generation for existing image generators, achieving performance comparable to state-of-the-art models and improving reasoning benchmarks.