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Review regressions before expanding the test." ], "measure": "Accepted draft length, tokens per second, tail latency, output quality, and total GPU 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": "2610.10411", "title": "Training Parallel Speculative Draft Models by Directly Minimizing Expected Decoding Rounds", "summary": "EDR replaces block-local surrogate losses (e.g., per-position distillation-style objectives) for training parallel/semi-autoregressive speculative drafters with a Markov-reward-process objective that directly minimizes expected decoding rounds, plus an exact offline evaluator for drafter comparison. 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