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Layer patching can dramatically enhance model performance in size interpolation, revealing that simple strategies often outperform complex methods.
A new trust score enables reliable evaluation of conditional generation samples even when reference distributions are absent, leading to better quality and performance in real-world applications.
Even with weaker assumptions, ICA post-processing can unlock state-of-the-art disentanglement from vanilla autoencoders and foundation model-scale MAEs.
