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Explicitly optimizing for target function smoothness can dramatically enhance the performance of models on tabular data.
Score estimation errors in vanilla diffusion models can lead to catastrophic failures in compositional generation, revealing a critical gap in current methodologies.
Concept extraction's identifiability problem just got a lot easier, thanks to a new framework that turns guarantee proofs into set intersection problems.
