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UC San Diego, Adobe Research
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Pixel diffusion鈥檚 chronic high-frequency blur is not an architectural bottleneck: a lightweight adversarial post-training phase restores natural spectral power laws without causing mode collapse or requiring changes to the sampling pipeline.
Current MLLMs struggle with complex physics reasoning, revealing critical gaps that OmniPhys aims to address with its extensive multimodal dataset.
Evolving data snapshots can boost LLM performance by over 20% in both intrinsic and extrinsic evaluations, reshaping how we approach human-centered AI alignment.
