Video2STL: Grounding VLM-Generated Temporal Specifications for Robot Learning
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摘自论文摘要
Video-based policy learning is particularly promising, as it illustrates target behaviors without requiring action annotations or embodiment-matched demonstrations. A central challenge is deciding what information should be transferred from the video to the robot.
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