A new VLA model called SI uses a four-step chain-of-thought to derive driving intent and applies it via classifier-free guidance to a flow-matching trajectory generator, showing competitive Waymo scores and intent-controllable plans.
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3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 3verdicts
UNVERDICTED 3representative citing papers
CNeVA combines variational behavior latents with rectified-flow generators and soft eligibility to deliver controllable yet realistic traffic simulation on Waymo data.
A consistency-regularized Euclidean-Wasserstein-2 gradient flow performs joint posterior sampling and prompt optimization in latent space for efficient low-NFE inverse problem solving with diffusion models.
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Consistency Regularised Gradient Flows for Inverse Problems
A consistency-regularized Euclidean-Wasserstein-2 gradient flow performs joint posterior sampling and prompt optimization in latent space for efficient low-NFE inverse problem solving with diffusion models.