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ConvergeFlow guarantees convergence to valid token embeddings, eliminating the need for cross-entropy supervision in flow-based language models.
Achieving provable posterior consistency with a simple, efficient algorithm that outperforms existing methods in image restoration tasks.
Adaptation to low-dimensional structures in diffusion models is surprisingly robust, thriving across a broad spectrum of update coefficients.
Diffusion models can provably learn complex, multi-modal data in high dimensions with near-optimal sample complexity, finally justifying their real-world performance.
