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Shanghai Jiao Tong University, Shanghai Innovation Institute
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Learning symbolic POMDPs from visual demonstrations allows robots to plan effectively under uncertainty, outperforming traditional methods in complex tasks.
Seedance 2.0 leapfrogs existing models by unifying multi-modal inputs (text, image, audio, video) into a single architecture for generating high-quality, longer-duration audio-video content.
