{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:U6TAUYGHFIMYO2Z6WL56NLKCWT","short_pith_number":"pith:U6TAUYGH","canonical_record":{"source":{"id":"2505.09264","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-05-14T10:25:14Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"07949b4e901f2cece5ddda67c1925009b927c8eb248c94bed96932a227f6858a","abstract_canon_sha256":"e210a9ee03f00a6942141cd7f5ecd0841a355d092dfb80a9f0f3b810db3dc34a"},"schema_version":"1.0"},"canonical_sha256":"a7a60a60c72a19876b3eb2fbe6ad42b4f5898abcac940b8b9e6d79d31d9bfe87","source":{"kind":"arxiv","id":"2505.09264","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.09264","created_at":"2026-07-05T11:03:05Z"},{"alias_kind":"arxiv_version","alias_value":"2505.09264v1","created_at":"2026-07-05T11:03:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.09264","created_at":"2026-07-05T11:03:05Z"},{"alias_kind":"pith_short_12","alias_value":"U6TAUYGHFIMY","created_at":"2026-07-05T11:03:05Z"},{"alias_kind":"pith_short_16","alias_value":"U6TAUYGHFIMYO2Z6","created_at":"2026-07-05T11:03:05Z"},{"alias_kind":"pith_short_8","alias_value":"U6TAUYGH","created_at":"2026-07-05T11:03:05Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:U6TAUYGHFIMYO2Z6WL56NLKCWT","target":"record","payload":{"canonical_record":{"source":{"id":"2505.09264","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-05-14T10:25:14Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"07949b4e901f2cece5ddda67c1925009b927c8eb248c94bed96932a227f6858a","abstract_canon_sha256":"e210a9ee03f00a6942141cd7f5ecd0841a355d092dfb80a9f0f3b810db3dc34a"},"schema_version":"1.0"},"canonical_sha256":"a7a60a60c72a19876b3eb2fbe6ad42b4f5898abcac940b8b9e6d79d31d9bfe87","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:03:05.257106Z","signature_b64":"Fu6qvp9QcpTLisg3cwlf/FOVAJ+VcP2nhVumNcxZjB0StR3YG73ZnFVkoiusWoLZ12T0jZVJP+bclhbW36+JCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a7a60a60c72a19876b3eb2fbe6ad42b4f5898abcac940b8b9e6d79d31d9bfe87","last_reissued_at":"2026-07-05T11:03:05.256607Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:03:05.256607Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.09264","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":"2026-07-05T11:03:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DH4vWT3fJOGCbX8yWf5oBQM4nln1xaCXWkfrLpWgcLslH1XeFvpakH46glTlfJYB8LqxhlVX+0b1IioJ4kV1DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T16:01:54.736167Z"},"content_sha256":"caa95b132b112a573e8948012eb9b8d9297d13727456219b22bd22aa555427a1","schema_version":"1.0","event_id":"sha256:caa95b132b112a573e8948012eb9b8d9297d13727456219b22bd22aa555427a1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:U6TAUYGHFIMYO2Z6WL56NLKCWT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning to Detect Multi-class Anomalies with Just One Normal Image Prompt","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Bin-Bin Gao","submitted_at":"2025-05-14T10:25:14Z","abstract_excerpt":"Unsupervised reconstruction networks using self-attention transformers have achieved state-of-the-art performance for multi-class (unified) anomaly detection with a single model. However, these self-attention reconstruction models primarily operate on target features, which may result in perfect reconstruction for both normal and anomaly features due to high consistency with context, leading to failure in detecting anomalies. Additionally, these models often produce inaccurate anomaly segmentation due to performing reconstruction in a low spatial resolution latent space. To enable reconstructi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.09264","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/2505.09264/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":"2026-07-05T11:03:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PzdcBC8wfG3VFowFxZNSYqGRL0uZqIEH+xbTrN9tZ1e7lG0rVRdK0q35c0wQcx10LQvOVBD3FJpIq/TbmXLyCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T16:01:54.736537Z"},"content_sha256":"2040caebaf50f28f4040ead3cc62d4b0a43136e6962a57f58577225f969d969f","schema_version":"1.0","event_id":"sha256:2040caebaf50f28f4040ead3cc62d4b0a43136e6962a57f58577225f969d969f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/U6TAUYGHFIMYO2Z6WL56NLKCWT/bundle.json","state_url":"https://pith.science/pith/U6TAUYGHFIMYO2Z6WL56NLKCWT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/U6TAUYGHFIMYO2Z6WL56NLKCWT/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":"2026-08-22T16:01:54Z","links":{"resolver":"https://pith.science/pith/U6TAUYGHFIMYO2Z6WL56NLKCWT","bundle":"https://pith.science/pith/U6TAUYGHFIMYO2Z6WL56NLKCWT/bundle.json","state":"https://pith.science/pith/U6TAUYGHFIMYO2Z6WL56NLKCWT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/U6TAUYGHFIMYO2Z6WL56NLKCWT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:U6TAUYGHFIMYO2Z6WL56NLKCWT","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":"e210a9ee03f00a6942141cd7f5ecd0841a355d092dfb80a9f0f3b810db3dc34a","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-05-14T10:25:14Z","title_canon_sha256":"07949b4e901f2cece5ddda67c1925009b927c8eb248c94bed96932a227f6858a"},"schema_version":"1.0","source":{"id":"2505.09264","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.09264","created_at":"2026-07-05T11:03:05Z"},{"alias_kind":"arxiv_version","alias_value":"2505.09264v1","created_at":"2026-07-05T11:03:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.09264","created_at":"2026-07-05T11:03:05Z"},{"alias_kind":"pith_short_12","alias_value":"U6TAUYGHFIMY","created_at":"2026-07-05T11:03:05Z"},{"alias_kind":"pith_short_16","alias_value":"U6TAUYGHFIMYO2Z6","created_at":"2026-07-05T11:03:05Z"},{"alias_kind":"pith_short_8","alias_value":"U6TAUYGH","created_at":"2026-07-05T11:03:05Z"}],"graph_snapshots":[{"event_id":"sha256:2040caebaf50f28f4040ead3cc62d4b0a43136e6962a57f58577225f969d969f","target":"graph","created_at":"2026-07-05T11:03:05Z","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/2505.09264/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Unsupervised reconstruction networks using self-attention transformers have achieved state-of-the-art performance for multi-class (unified) anomaly detection with a single model. However, these self-attention reconstruction models primarily operate on target features, which may result in perfect reconstruction for both normal and anomaly features due to high consistency with context, leading to failure in detecting anomalies. Additionally, these models often produce inaccurate anomaly segmentation due to performing reconstruction in a low spatial resolution latent space. To enable reconstructi","authors_text":"Bin-Bin Gao","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-05-14T10:25:14Z","title":"Learning to Detect Multi-class Anomalies with Just One Normal Image Prompt"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.09264","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:caa95b132b112a573e8948012eb9b8d9297d13727456219b22bd22aa555427a1","target":"record","created_at":"2026-07-05T11:03:05Z","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":"e210a9ee03f00a6942141cd7f5ecd0841a355d092dfb80a9f0f3b810db3dc34a","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-05-14T10:25:14Z","title_canon_sha256":"07949b4e901f2cece5ddda67c1925009b927c8eb248c94bed96932a227f6858a"},"schema_version":"1.0","source":{"id":"2505.09264","kind":"arxiv","version":1}},"canonical_sha256":"a7a60a60c72a19876b3eb2fbe6ad42b4f5898abcac940b8b9e6d79d31d9bfe87","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a7a60a60c72a19876b3eb2fbe6ad42b4f5898abcac940b8b9e6d79d31d9bfe87","first_computed_at":"2026-07-05T11:03:05.256607Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:03:05.256607Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Fu6qvp9QcpTLisg3cwlf/FOVAJ+VcP2nhVumNcxZjB0StR3YG73ZnFVkoiusWoLZ12T0jZVJP+bclhbW36+JCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:03:05.257106Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.09264","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:caa95b132b112a573e8948012eb9b8d9297d13727456219b22bd22aa555427a1","sha256:2040caebaf50f28f4040ead3cc62d4b0a43136e6962a57f58577225f969d969f"],"state_sha256":"ab32bac591843b5738f0ca0022e868af3da63cb13befb8546770c96a8d0c6d96"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kgtwxNUT5mT3/vMTZ1IuqIS+JAkD2/75F828v9nOmQe8HBg4ImNNALPM2DjWUWiPc4TApCz9AsPdPannwQ1uCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-22T16:01:54.739107Z","bundle_sha256":"8d3a34f1cb1707835eedb77004ec68c5cd0cc1d34cf76488d93037492bbd95e3"}}