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Review regressions before expanding the test." ], "measure": "Task quality, actual GPU memory, serving throughput, and preparation cost.", "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": "2609.21126", "title": "Layerwise Decoupling for Stable Structured Sparsification of Fully Connected Layers", "summary": "The method replaces joint, coupled penalization of all layers with a sequential layerwise scheme that extracts shallow two-layer subnetworks, normalizes inner weights, and applies a structured group penalty to prune neurons and reduce layer width. 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