{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:GWQYOZMFZYOJQDIVMF5RYI7T42","short_pith_number":"pith:GWQYOZMF","canonical_record":{"source":{"id":"2508.20829","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-08-28T14:25:07Z","cross_cats_sorted":[],"title_canon_sha256":"459071fca0ead4f64cf88916df30a64435477a406665bb5cf4d318bec9e6939d","abstract_canon_sha256":"c91bbb96a99a506a5b8d283b7901727094e8154a0429e465ecb75dfa5da716e0"},"schema_version":"1.0"},"canonical_sha256":"35a1876585ce1c980d15617b1c23f3e6b23832224b7f94cf5940118ff69d9bda","source":{"kind":"arxiv","id":"2508.20829","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.20829","created_at":"2026-07-05T12:01:11Z"},{"alias_kind":"arxiv_version","alias_value":"2508.20829v1","created_at":"2026-07-05T12:01:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.20829","created_at":"2026-07-05T12:01:11Z"},{"alias_kind":"pith_short_12","alias_value":"GWQYOZMFZYOJ","created_at":"2026-07-05T12:01:11Z"},{"alias_kind":"pith_short_16","alias_value":"GWQYOZMFZYOJQDIV","created_at":"2026-07-05T12:01:11Z"},{"alias_kind":"pith_short_8","alias_value":"GWQYOZMF","created_at":"2026-07-05T12:01:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:GWQYOZMFZYOJQDIVMF5RYI7T42","target":"record","payload":{"canonical_record":{"source":{"id":"2508.20829","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-08-28T14:25:07Z","cross_cats_sorted":[],"title_canon_sha256":"459071fca0ead4f64cf88916df30a64435477a406665bb5cf4d318bec9e6939d","abstract_canon_sha256":"c91bbb96a99a506a5b8d283b7901727094e8154a0429e465ecb75dfa5da716e0"},"schema_version":"1.0"},"canonical_sha256":"35a1876585ce1c980d15617b1c23f3e6b23832224b7f94cf5940118ff69d9bda","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T12:01:11.924867Z","signature_b64":"w3Cmp4+fV97WOLqeMO/P8LpNKSOhsT6ArasW8toQ8VehWm7wB5gjIHPtjQHlpYBslr1uuOzsEEtOdPcvKDCCCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"35a1876585ce1c980d15617b1c23f3e6b23832224b7f94cf5940118ff69d9bda","last_reissued_at":"2026-07-05T12:01:11.924381Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T12:01:11.924381Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2508.20829","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":"2026-07-05T12:01:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"P4wkMmcipX2yiGp/RcFO2Sj7JaNjWJNGmopjdfxF0OcSNnlMkwSW//2/Rn5Xv8BsP3uP/ADOCYHmyub8oQ51Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T04:38:59.749494Z"},"content_sha256":"fa827e7d0a40675be8c1d20ebed2dcc0067e872d179c651d33e6de4f80c62085","schema_version":"1.0","event_id":"sha256:fa827e7d0a40675be8c1d20ebed2dcc0067e872d179c651d33e6de4f80c62085"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:GWQYOZMFZYOJQDIVMF5RYI7T42","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ATM-GAD: Adaptive Temporal Motif Graph Anomaly Detection for Financial Transaction Networks","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Erkang Bao, Lin Song, Xiaoling Lv, Xinyue Wang, Zeyue Zhang","submitted_at":"2025-08-28T14:25:07Z","abstract_excerpt":"Financial fraud detection is essential to safeguard billions of dollars, yet the intertwined entities and fast-changing transaction behaviors in modern financial systems routinely defeat conventional machine learning models. Recent graph-based detectors make headway by representing transactions as networks, but they still overlook two fraud hallmarks rooted in time: (1) temporal motifs--recurring, telltale subgraphs that reveal suspicious money flows as they unfold--and (2) account-specific intervals of anomalous activity, when fraud surfaces only in short bursts unique to each entity. To expl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.20829","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/2508.20829/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":"2026-07-05T12:01:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ADVVNam11CDC+WQ7KVRWYWGCxyo0HHts9SHf26kbY0a33xf/aikk0jPm26QgKeJmU2+vzOwQ1e74ad+Ql8O2Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T04:38:59.750008Z"},"content_sha256":"bc7ec3a275bab714b2cd513fa3354632afb8e51d39868c2989dd38c5fc83d030","schema_version":"1.0","event_id":"sha256:bc7ec3a275bab714b2cd513fa3354632afb8e51d39868c2989dd38c5fc83d030"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GWQYOZMFZYOJQDIVMF5RYI7T42/bundle.json","state_url":"https://pith.science/pith/GWQYOZMFZYOJQDIVMF5RYI7T42/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GWQYOZMFZYOJQDIVMF5RYI7T42/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":"2026-08-11T04:38:59Z","links":{"resolver":"https://pith.science/pith/GWQYOZMFZYOJQDIVMF5RYI7T42","bundle":"https://pith.science/pith/GWQYOZMFZYOJQDIVMF5RYI7T42/bundle.json","state":"https://pith.science/pith/GWQYOZMFZYOJQDIVMF5RYI7T42/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GWQYOZMFZYOJQDIVMF5RYI7T42/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:GWQYOZMFZYOJQDIVMF5RYI7T42","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":"c91bbb96a99a506a5b8d283b7901727094e8154a0429e465ecb75dfa5da716e0","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-08-28T14:25:07Z","title_canon_sha256":"459071fca0ead4f64cf88916df30a64435477a406665bb5cf4d318bec9e6939d"},"schema_version":"1.0","source":{"id":"2508.20829","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.20829","created_at":"2026-07-05T12:01:11Z"},{"alias_kind":"arxiv_version","alias_value":"2508.20829v1","created_at":"2026-07-05T12:01:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.20829","created_at":"2026-07-05T12:01:11Z"},{"alias_kind":"pith_short_12","alias_value":"GWQYOZMFZYOJ","created_at":"2026-07-05T12:01:11Z"},{"alias_kind":"pith_short_16","alias_value":"GWQYOZMFZYOJQDIV","created_at":"2026-07-05T12:01:11Z"},{"alias_kind":"pith_short_8","alias_value":"GWQYOZMF","created_at":"2026-07-05T12:01:11Z"}],"graph_snapshots":[{"event_id":"sha256:bc7ec3a275bab714b2cd513fa3354632afb8e51d39868c2989dd38c5fc83d030","target":"graph","created_at":"2026-07-05T12:01:11Z","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/2508.20829/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Financial fraud detection is essential to safeguard billions of dollars, yet the intertwined entities and fast-changing transaction behaviors in modern financial systems routinely defeat conventional machine learning models. Recent graph-based detectors make headway by representing transactions as networks, but they still overlook two fraud hallmarks rooted in time: (1) temporal motifs--recurring, telltale subgraphs that reveal suspicious money flows as they unfold--and (2) account-specific intervals of anomalous activity, when fraud surfaces only in short bursts unique to each entity. To expl","authors_text":"Erkang Bao, Lin Song, Xiaoling Lv, Xinyue Wang, Zeyue Zhang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-08-28T14:25:07Z","title":"ATM-GAD: Adaptive Temporal Motif Graph Anomaly Detection for Financial Transaction Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.20829","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:fa827e7d0a40675be8c1d20ebed2dcc0067e872d179c651d33e6de4f80c62085","target":"record","created_at":"2026-07-05T12:01:11Z","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":"c91bbb96a99a506a5b8d283b7901727094e8154a0429e465ecb75dfa5da716e0","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-08-28T14:25:07Z","title_canon_sha256":"459071fca0ead4f64cf88916df30a64435477a406665bb5cf4d318bec9e6939d"},"schema_version":"1.0","source":{"id":"2508.20829","kind":"arxiv","version":1}},"canonical_sha256":"35a1876585ce1c980d15617b1c23f3e6b23832224b7f94cf5940118ff69d9bda","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"35a1876585ce1c980d15617b1c23f3e6b23832224b7f94cf5940118ff69d9bda","first_computed_at":"2026-07-05T12:01:11.924381Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T12:01:11.924381Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"w3Cmp4+fV97WOLqeMO/P8LpNKSOhsT6ArasW8toQ8VehWm7wB5gjIHPtjQHlpYBslr1uuOzsEEtOdPcvKDCCCg==","signature_status":"signed_v1","signed_at":"2026-07-05T12:01:11.924867Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.20829","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fa827e7d0a40675be8c1d20ebed2dcc0067e872d179c651d33e6de4f80c62085","sha256:bc7ec3a275bab714b2cd513fa3354632afb8e51d39868c2989dd38c5fc83d030"],"state_sha256":"c6f046fd5dec25c77ab15612ceaccaf707bcee90641a5a1c84789ccebbdbc168"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IXB1DwtOhcuEcZIguHYxjVCr6wWjJtTbekFNAICXzBUA6o58L9MOGiaX9JHT11CXZ29WupXMdMceWrwVdLoECg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T04:38:59.755313Z","bundle_sha256":"1dc4c19be1f896877d0826127d71bd9e7863f978de7641f0c55fabe83b7a1e0b"}}