Signed Symmetric Quantization for Few-Bit Integers

📰 ArXiv cs.AI

Learn how Signed Symmetric Quantization reduces quantization error for few-bit integers by adjusting the scale to account for the extra negative representable value

advanced Published 13 Jul 2026

Action Steps

Apply Signed Symmetric Quantization to few-bit integers using a custom scale
Compare the quantization error of standard symmetric quantization and Signed Symmetric Quantization
Configure the quantizer to assign the extra representable value to the positive tail
Test the effect of clipping on positive outliers using Signed Symmetric Quantization
Run experiments to evaluate the performance of Signed Symmetric Quantization at few-bit precision

Who Needs to Know This

Quantization engineers and researchers working with few-bit integers can benefit from this technique to improve the accuracy of their models

Key Insight

💡 Signed Symmetric Quantization adjusts the scale to account for the extra negative representable value, reducing clipping of positive outliers and quantization error

Key Takeaways

Learn how Signed Symmetric Quantization reduces quantization error for few-bit integers by adjusting the scale to account for the extra negative representable value

Full Article

Title: Signed Symmetric Quantization for Few-Bit Integers

Abstract:
arXiv:2607.08779v1 Announce Type: cross Abstract: The signed integer alphabet contains one more negative representable value than positive. Yet, by convention, the standard symmetric integer quantizer fixes its scale to be strictly positive, which assigns this extra representable value to the negative tail and can force clipping of positive outliers. In this work, we show that, at few-bit precision, such clipping is a non-trivial source of quantization error. Asymmetric quantization addresses th

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