Unverified50% confidenceFactExact time
DreamTrue builds an embodied video reward model to score the physical plausibility of predicted videos, and the scores are used for reinforcement learning post-training.
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10/12/2026
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UnverifiedDreamTrue introduces counterfactual post-training, which generates future videos under a broader range of action and contact configurations by modifying recorded action trajectories, in order to broaden interaction coverage.74% similarUnverifiedWorldGuide's experimental results show that coupling planning with learnable execution is key to goal-directed procedural video generation.73% similarUnverifiedThe training pipeline involves first training an image baseline model, using the image model to warm-start an eight-frame video baseline model, and ultimately generating 5.6-second inference outputs.69% similarVerifiedThe requirement for temporal coherence in video generation models compels the models to learn dynamics representations closer to the real world during training.69% similarVerifiedIn reinforcement learning training, the model's goal is to maximize the score given by the reward function.68% similar
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