{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:UKVQJ3QM3JY7U5SYGS2ONVSSHW","short_pith_number":"pith:UKVQJ3QM","schema_version":"1.0","canonical_sha256":"a2ab04ee0cda71fa765834b4e6d6523d98defa6a05b22396fc1392b07f71032c","source":{"kind":"arxiv","id":"2507.01417","version":2},"attestation_state":"computed","paper":{"title":"Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Jiawei Gu, Zechao Li, Ziyue Qiao","submitted_at":"2025-07-02T07:18:09Z","abstract_excerpt":"Out-of-Distribution (OOD) detection is critical for safely deploying deep models in open-world environments, where inputs may lie outside the training distribution. During inference on a model trained exclusively with In-Distribution (ID) data, we observe a salient gradient phenomenon: around an ID sample, the local gradient directions for \"enhancing\" that sample's predicted class remain relatively consistent, whereas OOD samples--unseen in training--exhibit disorganized or conflicting gradient directions in the same neighborhood. Motivated by this observation, we propose an inference-stage te"},"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":"2507.01417","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-07-02T07:18:09Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"f816112e903a926678f42094d3dcd41eba0ecc92cc38a6c0c3ddbc86bab4b95c","abstract_canon_sha256":"056a29f350751e9b9f2b477f2be6ad83b02e4818504d2b4456a6711964d31da2"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:31:47.195898Z","signature_b64":"CrBE8Hd6VJV7AUrMgnkqoPnodSvfeCGhcwdRqGX+M1ujpP+vwIzfHYIiCG+KCHSDurCBWs+AcHm+KLXPhzJYAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a2ab04ee0cda71fa765834b4e6d6523d98defa6a05b22396fc1392b07f71032c","last_reissued_at":"2026-07-05T11:31:47.195400Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:31:47.195400Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Jiawei Gu, Zechao Li, Ziyue Qiao","submitted_at":"2025-07-02T07:18:09Z","abstract_excerpt":"Out-of-Distribution (OOD) detection is critical for safely deploying deep models in open-world environments, where inputs may lie outside the training distribution. During inference on a model trained exclusively with In-Distribution (ID) data, we observe a salient gradient phenomenon: around an ID sample, the local gradient directions for \"enhancing\" that sample's predicted class remain relatively consistent, whereas OOD samples--unseen in training--exhibit disorganized or conflicting gradient directions in the same neighborhood. Motivated by this observation, we propose an inference-stage te"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.01417","kind":"arxiv","version":2},"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/2507.01417/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":"2507.01417","created_at":"2026-07-05T11:31:47.195465+00:00"},{"alias_kind":"arxiv_version","alias_value":"2507.01417v2","created_at":"2026-07-05T11:31:47.195465+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.01417","created_at":"2026-07-05T11:31:47.195465+00:00"},{"alias_kind":"pith_short_12","alias_value":"UKVQJ3QM3JY7","created_at":"2026-07-05T11:31:47.195465+00:00"},{"alias_kind":"pith_short_16","alias_value":"UKVQJ3QM3JY7U5SY","created_at":"2026-07-05T11:31:47.195465+00:00"},{"alias_kind":"pith_short_8","alias_value":"UKVQJ3QM","created_at":"2026-07-05T11:31:47.195465+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/UKVQJ3QM3JY7U5SYGS2ONVSSHW","json":"https://pith.science/pith/UKVQJ3QM3JY7U5SYGS2ONVSSHW.json","graph_json":"https://pith.science/api/pith-number/UKVQJ3QM3JY7U5SYGS2ONVSSHW/graph.json","events_json":"https://pith.science/api/pith-number/UKVQJ3QM3JY7U5SYGS2ONVSSHW/events.json","paper":"https://pith.science/paper/UKVQJ3QM"},"agent_actions":{"view_html":"https://pith.science/pith/UKVQJ3QM3JY7U5SYGS2ONVSSHW","download_json":"https://pith.science/pith/UKVQJ3QM3JY7U5SYGS2ONVSSHW.json","view_paper":"https://pith.science/paper/UKVQJ3QM","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2507.01417&json=true","fetch_graph":"https://pith.science/api/pith-number/UKVQJ3QM3JY7U5SYGS2ONVSSHW/graph.json","fetch_events":"https://pith.science/api/pith-number/UKVQJ3QM3JY7U5SYGS2ONVSSHW/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/UKVQJ3QM3JY7U5SYGS2ONVSSHW/action/timestamp_anchor","attest_storage":"https://pith.science/pith/UKVQJ3QM3JY7U5SYGS2ONVSSHW/action/storage_attestation","attest_author":"https://pith.science/pith/UKVQJ3QM3JY7U5SYGS2ONVSSHW/action/author_attestation","sign_citation":"https://pith.science/pith/UKVQJ3QM3JY7U5SYGS2ONVSSHW/action/citation_signature","submit_replication":"https://pith.science/pith/UKVQJ3QM3JY7U5SYGS2ONVSSHW/action/replication_record"}},"created_at":"2026-07-05T11:31:47.195465+00:00","updated_at":"2026-07-05T11:31:47.195465+00:00"}