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arXiv: cs.AI preprintsInternational11 November 2026

Precision on Demand: Escalating Weight Bits at Uncertain Decoding Steps in a Small Local Model

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arXiv:2611.14418v1 Announce Type: new Abstract: Local decoding usually fixes one weight precision for the whole generation. We study a different allocation: store 8-bit weights, decode with their top 4 bits, and redo a step at 8 bits only when the low-precision output distribution looks uncertain (entropy above a threshold or a small top-two margin). Quantization is simulated, the model is Qwen3-0.6B, and the benchmark is GSM8K. Cost is counted in weight bytes read per token. On 36724 replayed steps the entropy of the low pass ranks argmax flips with AUC 0.93. At a 15% escalation budget it cat
Source: arXiv: cs.AI preprints

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