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LMMs can learn to generate images *and* improve their understanding abilities, without catastrophic forgetting, by carefully disentangling and sharing experts within a MoE architecture.
End-to-end autonomous driving gets a boost with a new framework that links perception, prediction, and planning in a unified chain of thought, outperforming fragmented approaches.
LongCat-Next shatters the language-centric paradigm by unifying text, vision, and audio into a single autoregressive model with minimal modality-specific design, finally reconciling understanding and generation in discrete vision modeling.
