Author

Hongliang Li

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Jul 2026

Stable FP4 Training via Transposition-Invariant Block Quantization

This work proposes a low-precision training framework based on 2D block FP4 quantization, which enforces transposition-invariant scaling and preserves consistency between forward and backward computations, and combines this with truncation-free scaling and stochastic rounding to control quantization error and maintain unbiased gradients.

Mehdi Rahimifar, Amin Darabi, Mehran Taghian Jazi et al. · arXiv.org · 2 citations