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Unleashing the full potential of multimodal LLMs requires reasoning directly in the visual latent space, and this paper shows how to do it with stable policy optimization.
Synthesizing realistic hand-object interactions is now possible with HO-Flow, a framework that leverages masked flow matching and interaction-aware VAEs to achieve state-of-the-art results in motion diversity and physical plausibility.