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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": "2610.21742", "title": "Sparse Federated Echo State Networks for Time-Series Classification via Smooth-L1 Regularization", "summary": "Replaces the dense readout layer of Echo State Networks (and first-order federated averaging) with a Smooth-L1 regularized sparse readout trained via Newton's method, including a second-order federated aggregation scheme. 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