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By mixing flows and using a teacher-student approach, MMAE learns to classify encrypted traffic more accurately than previous masked autoencoders.
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.
