{"paper":{"title":"A Variational-Flow Analysis of StoRM under Noise-Power Mismatch","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"eess.AS","authors_text":"Shuubham Ojha","submitted_at":"2026-06-23T00:35:55Z","abstract_excerpt":"Diffusion-based speech enhancement architectures that pair a deterministic predictor with a learned score network, exhibit a sharp non-smooth transition (``kink'') in the SI-SDR degradation curve at the training-time noise amplitude. We give a pathwise variational-flow analysis that localizes this non-smoothness to the predictor stage. The central identity is an exact factorization of the parametric sensitivity, $\\partial \\sig^{(M)} / \\partial M = K(M) \\cdot \\partial C_M / \\partial M$, where $K(M)$ is a continuous matrix-valued functional of the score Jacobian along the reverse trajectory and "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.24035","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2606.24035/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}