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SportD opens a new direction for rigorously evaluating physical strategic decision-making in VLMs, showing that careful decomposition of their choices can reveal the mechanisms underlying systematic biases such as risk aversion.
This work introduces SUV, a unified end-to-end driving framework that casts future Scene Understanding as Video generation using a pretrained video foundation model, and shows that structured future supervision and direct future-stream access yield higher trajectory planning scores.
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