{"paper":{"title":"Reliability-Safety Trade-off in AI Distillation: A Renormalization-Group Approach","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cond-mat.stat-mech","authors_text":"C.P.Sun, Miao-Miao Yi, Tan-Ji Zhou, Y.M.Du","submitted_at":"2026-08-09T08:23:57Z","abstract_excerpt":"Knowledge distillation transfers more than task competence: it also transmits response propensities, refusal policies, error boundaries, and latent safety biases. We formulate this behavioral inheritance as a coarse-graining model grounded in statistical mechanics, in which the student's answer and refusal decisions define two macrostates, while the teacher induces an effective field that reshapes the student's free-energy landscape. The model yields a reliability-safety trade-off relation controlled by a single parameter K, which we term the hazard discrimination capability. The predicted tra"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.08572","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/2608.08572/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"}