{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:OGZB5EBQCDLY5ZSLSDIKHMWOAK","short_pith_number":"pith:OGZB5EBQ","schema_version":"1.0","canonical_sha256":"71b21e903010d78ee64b90d0a3b2ce02ab2678c3101c9b2a762a57778d383d40","source":{"kind":"arxiv","id":"2412.01596","version":1},"attestation_state":"computed","paper":{"title":"FEVER-OOD: Free Energy Vulnerability Elimination for Robust Out-of-Distribution Detection","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Brian K.S. Isaac-Medina, Mauricio Che, Samet Akcay, Toby P. Breckon, Yona F.A. Gaus","submitted_at":"2024-12-02T15:15:24Z","abstract_excerpt":"Modern machine learning models, that excel on computer vision tasks such as classification and object detection, are often overconfident in their predictions for Out-of-Distribution (OOD) examples, resulting in unpredictable behaviour for open-set environments. Recent works have demonstrated that the free energy score is an effective measure of uncertainty for OOD detection given its close relationship to the data distribution. However, despite free energy-based methods representing a significant empirical advance in OOD detection, our theoretical analysis reveals previously unexplored and inh"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2412.01596","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-12-02T15:15:24Z","cross_cats_sorted":[],"title_canon_sha256":"8ef182bc6856a573f4e9299cc3ae7954532d9b0c135189859d2bc80190a4450c","abstract_canon_sha256":"849d223a5e0e3da5887c4829446218bac131cac427bd83d2bf9a543feaa3dfab"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:43:15.960382Z","signature_b64":"WjfBHRxtuFvc0+E2CrI5xJ15zeCGutoPyXz/NOej7QEKt0/rm23tFsB2OeJ/PPI5bm6fxHF1As0x8AKwCYPwBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"71b21e903010d78ee64b90d0a3b2ce02ab2678c3101c9b2a762a57778d383d40","last_reissued_at":"2026-07-05T09:43:15.959795Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:43:15.959795Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"FEVER-OOD: Free Energy Vulnerability Elimination for Robust Out-of-Distribution Detection","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Brian K.S. Isaac-Medina, Mauricio Che, Samet Akcay, Toby P. Breckon, Yona F.A. Gaus","submitted_at":"2024-12-02T15:15:24Z","abstract_excerpt":"Modern machine learning models, that excel on computer vision tasks such as classification and object detection, are often overconfident in their predictions for Out-of-Distribution (OOD) examples, resulting in unpredictable behaviour for open-set environments. Recent works have demonstrated that the free energy score is an effective measure of uncertainty for OOD detection given its close relationship to the data distribution. However, despite free energy-based methods representing a significant empirical advance in OOD detection, our theoretical analysis reveals previously unexplored and inh"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.01596","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/2412.01596/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2412.01596","created_at":"2026-07-05T09:43:15.959855+00:00"},{"alias_kind":"arxiv_version","alias_value":"2412.01596v1","created_at":"2026-07-05T09:43:15.959855+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.01596","created_at":"2026-07-05T09:43:15.959855+00:00"},{"alias_kind":"pith_short_12","alias_value":"OGZB5EBQCDLY","created_at":"2026-07-05T09:43:15.959855+00:00"},{"alias_kind":"pith_short_16","alias_value":"OGZB5EBQCDLY5ZSL","created_at":"2026-07-05T09:43:15.959855+00:00"},{"alias_kind":"pith_short_8","alias_value":"OGZB5EBQ","created_at":"2026-07-05T09:43:15.959855+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/OGZB5EBQCDLY5ZSLSDIKHMWOAK","json":"https://pith.science/pith/OGZB5EBQCDLY5ZSLSDIKHMWOAK.json","graph_json":"https://pith.science/api/pith-number/OGZB5EBQCDLY5ZSLSDIKHMWOAK/graph.json","events_json":"https://pith.science/api/pith-number/OGZB5EBQCDLY5ZSLSDIKHMWOAK/events.json","paper":"https://pith.science/paper/OGZB5EBQ"},"agent_actions":{"view_html":"https://pith.science/pith/OGZB5EBQCDLY5ZSLSDIKHMWOAK","download_json":"https://pith.science/pith/OGZB5EBQCDLY5ZSLSDIKHMWOAK.json","view_paper":"https://pith.science/paper/OGZB5EBQ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2412.01596&json=true","fetch_graph":"https://pith.science/api/pith-number/OGZB5EBQCDLY5ZSLSDIKHMWOAK/graph.json","fetch_events":"https://pith.science/api/pith-number/OGZB5EBQCDLY5ZSLSDIKHMWOAK/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/OGZB5EBQCDLY5ZSLSDIKHMWOAK/action/timestamp_anchor","attest_storage":"https://pith.science/pith/OGZB5EBQCDLY5ZSLSDIKHMWOAK/action/storage_attestation","attest_author":"https://pith.science/pith/OGZB5EBQCDLY5ZSLSDIKHMWOAK/action/author_attestation","sign_citation":"https://pith.science/pith/OGZB5EBQCDLY5ZSLSDIKHMWOAK/action/citation_signature","submit_replication":"https://pith.science/pith/OGZB5EBQCDLY5ZSLSDIKHMWOAK/action/replication_record"}},"created_at":"2026-07-05T09:43:15.959855+00:00","updated_at":"2026-07-05T09:43:15.959855+00:00"}