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cs.RO2026
Learning Task-Invariant Properties via Dreamer: Enabling Efficient Policy Transfer for Quadruped Robots
Junyang Liang, Yuxuan Liu, Yabin Chang +5
Achieving quadruped robot locomotion across diverse and dynamic terrains presents significant challenges, primarily due to the discrepancies between simulation environments and rea…
cs.RO2026
ICLR: In-Context Imitation Learning with Visual Reasoning
Toan Nguyen, Weiduo Yuan, Songlin Wei +3
In-context imitation learning enables robots to adapt to new tasks from a small number of demonstrations without additional training. However, existing approaches typically conditi…