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Under review as a conference paper at ICLR 2027

Capability Is Not Utility: Context-Dependent Routing of Frozen Black-Box MIL Experts

Abstract

Routing among frozen heterogeneous experts is challenging because expert capability does not directly determine intervention utility. In computational pathology, independently trained multiple-instance learning (MIL) models often exhibit complementary strengths across patients, tasks, and expert sets, yet their relative usefulness can change with the evaluation context. We identify two key mismatches in capability-based routing: capability estimated from historical observations may not translate into anchor-relative decision utility, and expert preferences learned in one environment may not remain stable after transfer. We introduce EpiAtlas-Safe, a post-hoc routing framework for frozen black-box MIL experts. EpiAtlas-Safe combines episodic expert-set training, a two-region Capability Atlas for modeling heterogeneous expert behavior, and selective class-balanced safe coupling (SCSC) to align routing decisions with anchor-relative utility while reducing unreliable routing decisions. The framework operates only on class-probability predictions, enabling plug-compatible coordination of independently trained experts without accessing internal representations or joint retraining. On patient-disjoint CAMELYON+ and BRACS evaluations, EpiAtlas-Safe improves patient-weighted slide-level Macro-F1 over a matched capability-transfer router by 1.30 and 2.28 percentage points, respectively, with positive dataset-level gains across all fixed router seeds. In a separately held-out BRCA evaluation, it achieves a 1.08-point improvement on ER while remaining near parity on the prespecified ER/PAM50 primary-task average. Ablation studies support the contributions of SCSC and the Capability Atlas. Additional analyses of expert-ranking changes, utility variation, and residual oracle headroom support modeling expert capability as a context-dependent decision quantity rather than a static global score. Together, these results support viewing frozen-expert routing as context-dependent Anchor-relative intervention selection rather than direct transfer of a static capability ranking. Code is available at https://anonymous.4open.science/r/epiatlas-safe-review-6D07/README.md.

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