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C-PTQ reveals that harmonizing task sensitivity with quantization error can dramatically enhance MLLM performance without additional complexity.
Latent diffusion models can be significantly improved by matching the power spectral density between images and latents, unifying previous observations of over-noisy or over-smoothed latents under a single "Spectrum Matching Hypothesis."
