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Tri-modal masked diffusion models can now be trained from scratch, achieving strong results in text generation, text-to-image, and text-to-speech, thanks to a systematic exploration of the design space and a novel SDE-based batch size reparameterization.
Factually incorrect SLMs can be made more truthful by teaching them *what* to delegate, not just minimizing loss.
