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cs.RO2026
DREAM: Deployment-Time Demonstration Generation via Real-to-Sim for Scalable Policy Adaptation
Makoto Sato, Tatsuya Matsushima, Yutaka Matsuo +1
Vision-language-action (VLA) models have made strong progress in language-conditioned robot manipulation, but improving their performance in a new workspace still often requires ac…
cs.RO2026
SAIL: Test-Time Scaling for In-Context Imitation Learning with VLM
Makoto Sato, Yusuke Iwasawa, Yujin Tang +1
In-context imitation learning allows robots to acquire skills from demonstrations, yet one-shot trajectory generation remains fragile under environmental variation. We propose SAIL…