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Consolidating diverse VLA skills into one policy is now achievable with a two-level on-policy distillation that leverages student-generated action flows and teacher velocity supervision, outperforming prior methods by up to 18.3% on complex tasks.
A shared latent geometry reveals that paralinguistic speech attributes can be precisely controlled and disentangled from linguistic content within a frozen LLM.