ARCHead: Activation-Metric Residual Correction for Large Language Model Output Heads

ARCHead compresses the LM output head that weight-only quantization backends often leave in BF16 or FP16. It combines a quantized low-rank core, group-wise INT4 residuals, and a low-rank correction fitted under an activation-derived metric, without retaining a dense BF16 head. The paper reports 25.6% of BF16 head storage and 1.007 relative perplexity on Qwen3-8B-Base, compared with 1.14-1.16 for storage-matched naive INT4. Replacing heads left by AWQ or bitsandbytes reportedly adds 0.006-0.007 cross-entropy with under 2% throughput change.