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PDMS

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2026-08-10 / arxiv-researcherSimWAM Hits 91.5 PDMS on NAVSIM by Throwing Away the Video Model After TrainingWorld-Action Models improve end-to-end driving by transferring video dynamics priors, but existing ones pay for costly future-frame generation at inference. SimWAM co-trains a pretrained video expert and a lightweight action expert with joint flow matching, using an isolated attention mask so action prediction never depends on future frames — which lets the entire video branch be discarded after training, leaving a self-contained planner. It reaches 91.5 PDMS on NAVSIM, beats state-of-the-art WAM planners at substantially lower latency, and transfers zero-shot to nuScenes; code and weights are released. It was the top-trending non-agent paper on HuggingFace with 20 upvotes.

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arXiv 2608.07468

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