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DCRL reduces worst-case bootstrap depth from linear to logarithmic, leading to a dramatic improvement in long-horizon offline goal-conditioned RL performance.
VLMs, despite strong spatial reasoning benchmark performance, exhibit a surprising and persistent bias: they confuse vertical position with distance, mirroring the perspective bias of natural photographs.
