{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:FKB55IVNSU6JSBCESE275GWP4D","short_pith_number":"pith:FKB55IVN","canonical_record":{"source":{"id":"2502.01201","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-02-03T09:49:01Z","cross_cats_sorted":[],"title_canon_sha256":"8ae43be0a893e4f87340b632e17ffd919ac74d3fc9a0f2c42b0d7c59d61cadea","abstract_canon_sha256":"cb6e3b8686d072bded069e9f79c6088e3e64c0966c263dccc8ebd5896ac75d20"},"schema_version":"1.0"},"canonical_sha256":"2a83dea2ad953c9904449135fe9acfe0dbddb0d76cc5a4deaa02d4ecf055d301","source":{"kind":"arxiv","id":"2502.01201","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.01201","created_at":"2026-07-05T10:08:44Z"},{"alias_kind":"arxiv_version","alias_value":"2502.01201v1","created_at":"2026-07-05T10:08:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.01201","created_at":"2026-07-05T10:08:44Z"},{"alias_kind":"pith_short_12","alias_value":"FKB55IVNSU6J","created_at":"2026-07-05T10:08:44Z"},{"alias_kind":"pith_short_16","alias_value":"FKB55IVNSU6JSBCE","created_at":"2026-07-05T10:08:44Z"},{"alias_kind":"pith_short_8","alias_value":"FKB55IVN","created_at":"2026-07-05T10:08:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:FKB55IVNSU6JSBCESE275GWP4D","target":"record","payload":{"canonical_record":{"source":{"id":"2502.01201","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-02-03T09:49:01Z","cross_cats_sorted":[],"title_canon_sha256":"8ae43be0a893e4f87340b632e17ffd919ac74d3fc9a0f2c42b0d7c59d61cadea","abstract_canon_sha256":"cb6e3b8686d072bded069e9f79c6088e3e64c0966c263dccc8ebd5896ac75d20"},"schema_version":"1.0"},"canonical_sha256":"2a83dea2ad953c9904449135fe9acfe0dbddb0d76cc5a4deaa02d4ecf055d301","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:08:44.190868Z","signature_b64":"3VK8+kSCvbYi04g5+GLLIKbDgJyEdmnevEwj3iWdKwFahStCfi3vJB47gGM2mYlwRsAWAgAxxX+eAUuI2aICBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2a83dea2ad953c9904449135fe9acfe0dbddb0d76cc5a4deaa02d4ecf055d301","last_reissued_at":"2026-07-05T10:08:44.190460Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:08:44.190460Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2502.01201","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:08:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uZoltVaOGQt8G1T1blSsJ0jCkn7rkt70Mbi2R03vA0Q88GA4cO+g7hDQoBfUhkV8dROOO7evAGKTM10Cyt2aDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T11:30:08.245850Z"},"content_sha256":"50d765f1da71b24edc2853c6f8d2824f2906d706ab061bb6272cac233d3fee97","schema_version":"1.0","event_id":"sha256:50d765f1da71b24edc2853c6f8d2824f2906d706ab061bb6272cac233d3fee97"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:FKB55IVNSU6JSBCESE275GWP4D","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"One-to-Normal: Anomaly Personalization for Few-shot Anomaly Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Kang Li, Qicheng Lao, Shaoting Zhang, Yiyue Li","submitted_at":"2025-02-03T09:49:01Z","abstract_excerpt":"Traditional Anomaly Detection (AD) methods have predominantly relied on unsupervised learning from extensive normal data. Recent AD methods have evolved with the advent of large pre-trained vision-language models, enhancing few-shot anomaly detection capabilities. However, these latest AD methods still exhibit limitations in accuracy improvement. One contributing factor is their direct comparison of a query image's features with those of few-shot normal images. This direct comparison often leads to a loss of precision and complicates the extension of these techniques to more complex domains--a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.01201","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/2502.01201/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:08:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eBJuRMqbxYKgIkVERfP6zaQM2jr4PTe4NZ6YkbIZAjM+xYkwprJ0jyFUOW0AVTk3pnYrLvky0igxwwDVgtnUBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T11:30:08.246422Z"},"content_sha256":"3a08fe05984559267da8ef822e0c13d9806cc1ec6401d3624e452bbc45d5d1b2","schema_version":"1.0","event_id":"sha256:3a08fe05984559267da8ef822e0c13d9806cc1ec6401d3624e452bbc45d5d1b2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FKB55IVNSU6JSBCESE275GWP4D/bundle.json","state_url":"https://pith.science/pith/FKB55IVNSU6JSBCESE275GWP4D/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FKB55IVNSU6JSBCESE275GWP4D/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-10T11:30:08Z","links":{"resolver":"https://pith.science/pith/FKB55IVNSU6JSBCESE275GWP4D","bundle":"https://pith.science/pith/FKB55IVNSU6JSBCESE275GWP4D/bundle.json","state":"https://pith.science/pith/FKB55IVNSU6JSBCESE275GWP4D/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FKB55IVNSU6JSBCESE275GWP4D/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:FKB55IVNSU6JSBCESE275GWP4D","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":"cb6e3b8686d072bded069e9f79c6088e3e64c0966c263dccc8ebd5896ac75d20","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-02-03T09:49:01Z","title_canon_sha256":"8ae43be0a893e4f87340b632e17ffd919ac74d3fc9a0f2c42b0d7c59d61cadea"},"schema_version":"1.0","source":{"id":"2502.01201","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.01201","created_at":"2026-07-05T10:08:44Z"},{"alias_kind":"arxiv_version","alias_value":"2502.01201v1","created_at":"2026-07-05T10:08:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.01201","created_at":"2026-07-05T10:08:44Z"},{"alias_kind":"pith_short_12","alias_value":"FKB55IVNSU6J","created_at":"2026-07-05T10:08:44Z"},{"alias_kind":"pith_short_16","alias_value":"FKB55IVNSU6JSBCE","created_at":"2026-07-05T10:08:44Z"},{"alias_kind":"pith_short_8","alias_value":"FKB55IVN","created_at":"2026-07-05T10:08:44Z"}],"graph_snapshots":[{"event_id":"sha256:3a08fe05984559267da8ef822e0c13d9806cc1ec6401d3624e452bbc45d5d1b2","target":"graph","created_at":"2026-07-05T10:08:44Z","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/2502.01201/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Traditional Anomaly Detection (AD) methods have predominantly relied on unsupervised learning from extensive normal data. Recent AD methods have evolved with the advent of large pre-trained vision-language models, enhancing few-shot anomaly detection capabilities. However, these latest AD methods still exhibit limitations in accuracy improvement. One contributing factor is their direct comparison of a query image's features with those of few-shot normal images. This direct comparison often leads to a loss of precision and complicates the extension of these techniques to more complex domains--a","authors_text":"Kang Li, Qicheng Lao, Shaoting Zhang, Yiyue Li","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-02-03T09:49:01Z","title":"One-to-Normal: Anomaly Personalization for Few-shot Anomaly Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.01201","kind":"arxiv","version":1},"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":"sha256:50d765f1da71b24edc2853c6f8d2824f2906d706ab061bb6272cac233d3fee97","target":"record","created_at":"2026-07-05T10:08:44Z","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":"cb6e3b8686d072bded069e9f79c6088e3e64c0966c263dccc8ebd5896ac75d20","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-02-03T09:49:01Z","title_canon_sha256":"8ae43be0a893e4f87340b632e17ffd919ac74d3fc9a0f2c42b0d7c59d61cadea"},"schema_version":"1.0","source":{"id":"2502.01201","kind":"arxiv","version":1}},"canonical_sha256":"2a83dea2ad953c9904449135fe9acfe0dbddb0d76cc5a4deaa02d4ecf055d301","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2a83dea2ad953c9904449135fe9acfe0dbddb0d76cc5a4deaa02d4ecf055d301","first_computed_at":"2026-07-05T10:08:44.190460Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:08:44.190460Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"3VK8+kSCvbYi04g5+GLLIKbDgJyEdmnevEwj3iWdKwFahStCfi3vJB47gGM2mYlwRsAWAgAxxX+eAUuI2aICBw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:08:44.190868Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.01201","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:50d765f1da71b24edc2853c6f8d2824f2906d706ab061bb6272cac233d3fee97","sha256:3a08fe05984559267da8ef822e0c13d9806cc1ec6401d3624e452bbc45d5d1b2"],"state_sha256":"b98d94c32e9b6349661015ccb69709f4118b080f82e245a29b83709d97c8b79d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TBU+eEKbxIjwPDzQ1fW76JIPOkSlXEEzR63hPH3H+VFQeupp6cjgQq0lgQhETRhmLBSdu07plE3ycekhb7THDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T11:30:08.250901Z","bundle_sha256":"53a01766152b8bb0d56890742166e9d25e3ae2e02ca6ff2c76b1bfcc84d0510b"}}