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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.
DyLaR is proposed, which first grounds a question in a short block of perception latents, and then adaptively decides whether to append reasoning latents before answering, and which improves average accuracy over same-backbone baselines while generating fewer than 20 tokens per query.
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