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Author

Mostafa Kotb

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Preprint Oct 2026

DreamFormer: Dream Imitation with a Transformer World Model for Language-Conditioned Robotic Manipulation

DreamFormer first learns a task-agnostic Transformer world model from unstructured play data, then acquires task-specific behaviors by optimizing an intrinsic reward that aligns agent-generated rollouts with expert demonstrations within the latent imagination of a learned world model.

Mostafa Kotb, C. Weber, Muhammad Burhan Hafez et al. · 0 citations

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