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News/Benford's Law as a Distributional Prior for Post-Training Quantization of Large Language Models
arxiv
PublishedSeptember 14, 2026 at 4:00 AM
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Benford's Law as a Distributional Prior for Post-Training Quantization of Large Language Models

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arXiv:2602.00165v2 Announce Type: replace Abstract: Post-training quantization (PTQ) is a practical way to reduce the memory footprint of large language models, but low-bit quantization is sensitive to mismatches between the quantization codebook and the empirical weight/activation distributions. We

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