Cost-Aware Hierarchical Evidence Routing for Molecular Retrieval from Mass Spectra

Molecular retrieval from tandem mass spectra aims to rank candidate structures based on their compatibility with observed fragmentation patterns. Existing approaches based on global spectrum–molecule representations do not adequately distinguish candidates with subtle structural differences and therefore struggle to rank structurally similar molecules accurately. Fine-grained structural evidence can improve discrimination among these candidates, but uniformly evaluating such evidence for all candidates incurs substantial computational costs and overlooks query-specific refinement needs. To address this challenge, we propose MS-CHER, a two-stage molecular retrieval framework with Cost-aware Hierarchical Evidence Routing. The key idea is to tailor fine-grained evidence computation to the refinement needs of each query. We obtain an initial candidate ranking through global spectrum–molecule matching using structure-aware molecular representations. Building on this ranking, a hierarchical routing policy determines a query-dependent refinement scope and selectively activates structural evidence within this scope according to predicted ranking benefits and computational costs. Experiments on multiple MS/MS retrieval benchmarks demonstrate competitive retrieval performance across diverse candidate settings. Notably, compared with exhaustive evidence evaluation on MassSpecGym, MS-CHER reduces structural evidence evaluation runtime by approximately 79.2% and 82.4% in the mass and formula settings, respectively, while maintaining comparable retrieval accuracy.