{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:7HJRWUWDLTUI4FP6FRXCUSMUK4","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"cc2c50ca4a57e34890eaea2c34d4a2b4f0bf08af013673850864fe93cb07148c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-04-17T14:22:27Z","title_canon_sha256":"f54584476033b918bfef03d8a091e9bcafb0d77827e090a001b50e5e7ae11fee"},"schema_version":"1.0","source":{"id":"2504.12970","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.12970","created_at":"2026-07-05T11:48:02Z"},{"alias_kind":"arxiv_version","alias_value":"2504.12970v2","created_at":"2026-07-05T11:48:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.12970","created_at":"2026-07-05T11:48:02Z"},{"alias_kind":"pith_short_12","alias_value":"7HJRWUWDLTUI","created_at":"2026-07-05T11:48:02Z"},{"alias_kind":"pith_short_16","alias_value":"7HJRWUWDLTUI4FP6","created_at":"2026-07-05T11:48:02Z"},{"alias_kind":"pith_short_8","alias_value":"7HJRWUWD","created_at":"2026-07-05T11:48:02Z"}],"graph_snapshots":[{"event_id":"sha256:2c62e2dafb2a6cf805ed63b526615f198108b22d6eefbd9cbe95355623b40daf","target":"graph","created_at":"2026-07-05T11:48:02Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2504.12970/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Currently, industrial anomaly detection suffers from two bottlenecks: (i) the rarity of real-world defect images and (ii) the opacity of sample quality when synthetic data are used. Existing synthetic strategies (e.g., cut-and-paste) overlook the underlying physical causes of defects, leading to inconsistent, low-fidelity anomalies that hamper model generalization to real-world complexities. In this paper, we introduce a novel and lightweight pipeline that generates synthetic anomalies through Math-Phys model guidance, refines them via a Coarse-to-Fine approach and employs a bi-level optimizat","authors_text":"Bingke Zhu, Jinqiao Wang, Long Qian, Ming Tang, Yingying Chen","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-04-17T14:22:27Z","title":"MathPhys-Guided Coarse-to-Fine Anomaly Synthesis with SQE-Driven Bi-Level Optimization for Anomaly Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.12970","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:4a3ceba6eec4f016abc9d91d9833f3d64d6e58e24eab005bffbf1514ffe6c911","target":"record","created_at":"2026-07-05T11:48:02Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"cc2c50ca4a57e34890eaea2c34d4a2b4f0bf08af013673850864fe93cb07148c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-04-17T14:22:27Z","title_canon_sha256":"f54584476033b918bfef03d8a091e9bcafb0d77827e090a001b50e5e7ae11fee"},"schema_version":"1.0","source":{"id":"2504.12970","kind":"arxiv","version":2}},"canonical_sha256":"f9d31b52c35ce88e15fe2c6e2a4994570ab28c14047afde666ea3d11cf1eec6e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f9d31b52c35ce88e15fe2c6e2a4994570ab28c14047afde666ea3d11cf1eec6e","first_computed_at":"2026-07-05T11:48:02.607243Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:48:02.607243Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"F/vLK8eetsKuO6BZTCof7kn7OZvcj/BIM5cLlSBGDY/jhHtGnmRP0N6uybNkhYW/g/TpOMN7JQXkLBgqLK0sAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:48:02.607742Z","signed_message":"canonical_sha256_bytes"},"source_id":"2504.12970","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4a3ceba6eec4f016abc9d91d9833f3d64d6e58e24eab005bffbf1514ffe6c911","sha256:2c62e2dafb2a6cf805ed63b526615f198108b22d6eefbd9cbe95355623b40daf"],"state_sha256":"b87c6319ab37dadc76c98afd94507b2def08a3c89c44217b070defd545413975"}