ROUTEAUDIT: Interaction-Aware Identification for Budgeted Multi-Verifier Routing
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Computer Science > Artificial Intelligence
arXiv:2610.02808 (cs)
[Submitted on 2 Oct 2026]
Title:ROUTEAUDIT: Interaction-Aware Identification for Budgeted Multi-Verifier Routing
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Abstract:Adaptive multi-verifier systems are commonly compared through endpoint quality-cost gaps, even when the verifier catalog, availability, accounting, information filtration, or scorer changes with the policy. We formulate verifier routing as a contract-conditioned identification problem. The contract records request support, verifier catalog, realized availability, resource accounting, online filtration, and post-trace scoring; a matched route contrast changes only the policy coordinate. ROUTEAUDIT adds three measurable objects to this contract. A contract lattice averages coordinate increments over every admissible bridge order and reports the resulting attribution together with its path sensitivity. A policy-independent response tape identifies paired sequential contrasts when adaptive policies reveal different observations. For incomplete matching, request-level bounds use whichever potential outcome remains observed and give a sharp finite-population interval. The protocol commits paid observations and ledger events before the oracle join and returns an attribution certificate for each comparison. On two held-out raw-tail caches, matched static SF+SA equals the cascade, assigning the apparent gains of 0.1797 and 0.1250 over full static to the verifier-set edge. On 1,319 held-out task requests, the learned and RLVR studies report quality 0.9522 and 0.9553 versus 0.9484 for matched static; the RLVR-static paired difference is +0.0068 with a request-paired interval $[0.0015,0.0122]$ and a training-seed-by-request hierarchical interval $[0.0006,0.0131]$. Controlled attribution recovery yields route mean absolute error 0.0011 and endpoint reconstruction error 0.0004. Factorial, bridge-order, and stochastic-provider studies evaluate the certificate interface; RLVR supplies a learned-policy stress test under the same identification contract.
| Comments: | 45 pages, 15 figures |
| Subjects: | Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Machine Learning (cs.LG) |
| Cite as: | arXiv:2610.02808 [cs.AI] |
| (or arXiv:2610.02808v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2610.02808
arXiv-issued DOI via DataCite (pending registration)
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View a PDF of the paper titled ROUTEAUDIT: Interaction-Aware Identification for Budgeted Multi-Verifier Routing, by Miaobo Hu and 7 other authors
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