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Review regressions before expanding the test." ], "measure": "Agreement with human review, missed failures, false alarms, and evaluation cost per task.", "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": "2609.18909", "title": "Beyond Outcomes: Dual-View Relational Learning for Efficient Agent Benchmarking", "summary": "It replaces full agent benchmark runs with a small exact-size miniset selected by jointly modeling outcome and process (trajectory) relations, from which full-benchmark scores are predicted. The cost is collecting and featurizing large-scale historical trajectories across agents, training the relational predictor, and maintaining six process signals per task. 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