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Prior claims of SVD-based compression effectiveness crumble under standardized evaluation, revealing that performance varies dramatically across models and setups.
Diffusion models can run over 3x faster without retraining or architectural changes, thanks to a clever second-order prediction scheme.
LLMs struggle to extract and reason over complex text structures in scientific domains, but explicitly prompting them to build these structures first yields significant performance gains.
