Pushing the Limits of Block Rotations in Post-Training Quantization
📰 ArXiv cs.AI
Learn how block rotations impact post-training quantization and reduce outliers using block Hadamard rotations
Action Steps
- Apply block Hadamard rotations to diffuse outliers in post-training quantization
- Analyze the effect of block structure on outlier suppression
- Use non-asymptotic analysis to understand the impact of block rotations on model performance
- Implement block rotations in PTQ methods to reduce online full-vector rotations overhead
- Evaluate the trade-off between outlier suppression and computational overhead
Who Needs to Know This
ML engineers and researchers working on post-training quantization methods can benefit from this knowledge to improve model performance and efficiency
Key Insight
💡 Block Hadamard rotations can effectively suppress outliers in post-training quantization, reducing computational overhead
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Pushing the limits of block rotations in post-training quantization #PTQ #ML
Key Takeaways
Learn how block rotations impact post-training quantization and reduce outliers using block Hadamard rotations
Full Article
Title: Pushing the Limits of Block Rotations in Post-Training Quantization
Abstract:
arXiv:2601.22347v2 Announce Type: replace-cross 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 fund
Abstract:
arXiv:2601.22347v2 Announce Type: replace-cross 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 fund
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