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Review regressions before expanding the test." ], "measure": "Peak memory, task pass rate, latency, and total serving cost at the same context and load.", "decision": "Keep the change only if it meets your preselected quality and latency limits and improves the metric you care about after setup and operating costs. Otherwise retain the baseline. This is an exploration plan, not a validated recommendation." }, "builder_review": null, "arxiv_id": "2610.20303", "title": "SpectrumQuant: Spectrum Alignment for LLM Quantization", "summary": "SpectrumQuant replaces calibration-time optimized learned rotations (SpinQuant, DartQuant) with a closed-form orthogonal transform built from estimated activation covariance, bridging fixed Hadamard rotations and learned rotations for post-training quantization. It costs a calibration pass to estimate covariance and adds the transform computation, but uses less than one-third of the GPU memory of learned-rotation approaches and no rotation training. 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