Stopping and Routing LLM Judge Panels
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Computer Science > Computation and Language
Title:Stopping and Routing LLM Judge Panels
Abstract:LLM evaluation pipelines often have many candidate judges: general LLM-as-a-judge prompts, reward models, safety classifiers, confidence variants, and task-specific verifiers. The deployment question is not only which judge is best, but which judges should be called, on which examples, and when panel construction should stop. We formulate judge-panel design as a role-conditioned allocation problem. From a small labeled audit set, declared slices, and judge costs, the method estimates target-relative roles: copies add no conditional information, complements improve the global panel, and specialists help only on slices. These roles induce a policy: drop copies, add complements globally, route specialists conditionally, and stop when validation gain falls below a threshold. Across reasoning, code, safety, preference, reward-model, summarization, and math audits, the method is compared with single judges, flat panels, matched diversity heuristics, full-call stacking, reliability juries, and frugal cascades. The result is a regime map for judge calls: route specialists on deployable slices, stop in saturated verifier regimes, keep broad ensembles when their risk benefit is worth the cost, and ignore conditional copies. The output is a reusable, auditable call plan for the next evaluation batch.
| Comments: | 21 pages, 2 figures, 20 tables. Accepted at WISE 2026 |
| Subjects: | Computation and Language (cs.CL) |
| Cite as: | arXiv:2608.19802 [cs.CL] |
| (or arXiv:2608.19802v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2608.19802
arXiv-issued DOI via DataCite (pending registration)
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