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Generate realistic and controllable videos of humans interacting with objects using only sparse motion cues, like wrist positions and object bounding boxes.
LLMs can match SOTA supervised theorem provers without training, if you give them the right structural scaffolding.
Task-oriented dialogue agents can now learn to balance user satisfaction and operational costs, thanks to a new RL framework that optimizes for both.
By explicitly aligning intra-modality relationships, SSR$^2$-GCD unlocks more effective cross-modal representation learning for generalized category discovery.
