Self-distillation from a caption-conditioned video diffusion model to an image-and-prompt-conditioned executor, enhanced by RL from VLM feedback, enables task solving in world models.
From generation to generalization: Emergent few-shot learning in video diffusion models
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Converting 3D MRI volumes into action-conditioned 2D slice navigation sequences offers a complementary self-supervised pretraining signal for learning anatomical and spatial representations.
Generative video models exhibit emergent zero-shot capabilities across perception, manipulation, and basic reasoning tasks.
citing papers explorer
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World Model Self-Distillation: Training World Models to Solve General Tasks
Self-distillation from a caption-conditioned video diffusion model to an image-and-prompt-conditioned executor, enhanced by RL from VLM feedback, enables task solving in world models.
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3D MRI Image Pretraining via Controllable 2D Slice Navigation Task
Converting 3D MRI volumes into action-conditioned 2D slice navigation sequences offers a complementary self-supervised pretraining signal for learning anatomical and spatial representations.
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Video models are zero-shot learners and reasoners
Generative video models exhibit emergent zero-shot capabilities across perception, manipulation, and basic reasoning tasks.