Pushing the Limits of Block Rotations in Post-Training Quantization

arXiv:2601.22347v2 Announce Type: replace Abstract: Recent post-training quantization (PTQ) methods have adopted block rotations to diffuse outliers prior to rounding. While this reduces the overhead of online full-vector rotations, the effect of block structure on outlier suppression remains poorly understood. To fill this gap, we present the first systematic, non-asymptotic analysis of outlier suppression for block Hadamard rotations. Our analysis reveals that outlier suppression is fundamentally limited by the geometry of the input vector. In particular, in the deterministic worst case, pos

Source: arXiv cs.LG — read the full report at the original publisher.

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