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Lin and colleagues: activation-aware weight quantization

Contribution grade

Efficient language-model inference · Human-designed research method or resource

Reference score120,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Used activation statistics and equivalent channel scaling to protect salient weight channels during low-bit weight-only quantization.

Scientific scope

Used activation statistics and equivalent channel scaling to protect salient weight channels during low-bit weight-only quantization. Year follows the 2023 preprint; MLSys publication was 2024. The technique and accompanying TinyChat system form one package; reported gains are workload- and hardware-specific.

Evidence

The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Year follows the 2023 preprint; MLSys publication was 2024. The technique and accompanying TinyChat system form one package; reported gains are workload- and hardware-specific.

Contributors

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

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