Activation-Weighted Seeded Residual Coding for Low-Bit LLM Weight Repair

Abstract:Low-bit weight quantization saves storage but leaves errors that degrade language-model quality. We introduce Activation-Weighted Seeded Residual Coding (AWSRC), a compact repair codec for an existing quantization backbone. Given a reconstructed weight $W_0$, AWSRC encodes the residual $W-W_0$ using deterministic seed-generated bases. The sidecar stores seed selectors, low-bit coefficients, and scales rather than an explicit codebook. Activation statistics prioritize errors that affect layer outputs. On Qwen2.5-3B-Instruct, adding 0.162 scope-bits/weight to an INT4 RTN backbone closes 88.2%, 78.9%, and 71.3% of the matched PPL, KL, and accuracy gaps to BF16. Repairing a matched strong low-bit backbone also improves all measured quality metrics. With a matched 49.25 MB sidecar, about 0.8% of the BF16 model-weight payload, AWSRC gives the best perplexity and mean task accuracy among sparse, low-rank, and vector-quantized codecs.

Machine Learning (cs.LG); Computation and Language (cs.CL)

arXiv:2608.23144 [cs.LG]

(or arXiv:2608.23144v1 [cs.LG] for this version)

https://doi.org/10.48550/arXiv.2608.23144 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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