{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:YB4Q7OVMJWTNT2NIFRJTGSLPXE","short_pith_number":"pith:YB4Q7OVM","canonical_record":{"source":{"id":"2506.00654","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2025-05-31T17:47:29Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"7abe289b08f300daef5bf4c19f293de71f687e97d5c83f272fff1f99bf5a71a9","abstract_canon_sha256":"73b96f6885e1e6ea4c6512374b286817c0a6926bd17982b61469997c66857781"},"schema_version":"1.0"},"canonical_sha256":"c0790fbaac4da6d9e9a82c5333496fb927966f41b56d2b2f2fa4a6678bbe0f41","source":{"kind":"arxiv","id":"2506.00654","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.00654","created_at":"2026-07-05T11:17:46Z"},{"alias_kind":"arxiv_version","alias_value":"2506.00654v1","created_at":"2026-07-05T11:17:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.00654","created_at":"2026-07-05T11:17:46Z"},{"alias_kind":"pith_short_12","alias_value":"YB4Q7OVMJWTN","created_at":"2026-07-05T11:17:46Z"},{"alias_kind":"pith_short_16","alias_value":"YB4Q7OVMJWTNT2NI","created_at":"2026-07-05T11:17:46Z"},{"alias_kind":"pith_short_8","alias_value":"YB4Q7OVM","created_at":"2026-07-05T11:17:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:YB4Q7OVMJWTNT2NIFRJTGSLPXE","target":"record","payload":{"canonical_record":{"source":{"id":"2506.00654","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2025-05-31T17:47:29Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"7abe289b08f300daef5bf4c19f293de71f687e97d5c83f272fff1f99bf5a71a9","abstract_canon_sha256":"73b96f6885e1e6ea4c6512374b286817c0a6926bd17982b61469997c66857781"},"schema_version":"1.0"},"canonical_sha256":"c0790fbaac4da6d9e9a82c5333496fb927966f41b56d2b2f2fa4a6678bbe0f41","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:17:46.608289Z","signature_b64":"Jq5bChX7Sr/6YKWtE0ULg0zH9UGJlfzxAIGSKHRiqFiLgfj/dcppP1W9GT5racX8f3tq91Q2s4hK2bvvb8OXCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c0790fbaac4da6d9e9a82c5333496fb927966f41b56d2b2f2fa4a6678bbe0f41","last_reissued_at":"2026-07-05T11:17:46.607792Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:17:46.607792Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.00654","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":"2026-07-05T11:17:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sLy1BfaUXOXHlaH3GrTxeB4N1gsJZxTT3TpLK3Ka3HHsJHAcDyS/X9tlyPvb4wD/LZObiEaBgTBv5mGRnEGDCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T23:54:21.381960Z"},"content_sha256":"f2450eedcb2464120916af08ef7e2997852814cb0fe6753c5af0968b63fbb39d","schema_version":"1.0","event_id":"sha256:f2450eedcb2464120916af08ef7e2997852814cb0fe6753c5af0968b63fbb39d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:YB4Q7OVMJWTNT2NIFRJTGSLPXE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CR","authors_text":"Francesco Panebianco, Marco Di Gennaro, Marco Pianta, Michele Carminati, Stefano Zanero","submitted_at":"2025-05-31T17:47:29Z","abstract_excerpt":"Money laundering is a financial crime that poses a serious threat to financial integrity and social security. The growing number of transactions makes it necessary to use automatic tools that help law enforcement agencies detect such criminal activity. In this work, we present Amatriciana, a novel approach based on Graph Neural Networks to detect money launderers inside a graph of transactions by considering temporal information. Amatriciana uses the whole graph of transactions without splitting it into several time-based subgraphs, exploiting all relational information in the dataset. Our exp"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.00654","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/2506.00654/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":"2026-07-05T11:17:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pVWcKtNPbpwo+Cv+WApTlnOyd5ipEX1BmK/avAivoj57E6U7ndZxTllO5wab/W3olwsB5qWjaPkZOfJYFatCAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T23:54:21.382521Z"},"content_sha256":"a31f83ee21ce2be00c270aa3e5505a4533e170f6712c836cf2797f6bb1ce9488","schema_version":"1.0","event_id":"sha256:a31f83ee21ce2be00c270aa3e5505a4533e170f6712c836cf2797f6bb1ce9488"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YB4Q7OVMJWTNT2NIFRJTGSLPXE/bundle.json","state_url":"https://pith.science/pith/YB4Q7OVMJWTNT2NIFRJTGSLPXE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YB4Q7OVMJWTNT2NIFRJTGSLPXE/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":"2026-08-07T23:54:21Z","links":{"resolver":"https://pith.science/pith/YB4Q7OVMJWTNT2NIFRJTGSLPXE","bundle":"https://pith.science/pith/YB4Q7OVMJWTNT2NIFRJTGSLPXE/bundle.json","state":"https://pith.science/pith/YB4Q7OVMJWTNT2NIFRJTGSLPXE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YB4Q7OVMJWTNT2NIFRJTGSLPXE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:YB4Q7OVMJWTNT2NIFRJTGSLPXE","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":"73b96f6885e1e6ea4c6512374b286817c0a6926bd17982b61469997c66857781","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2025-05-31T17:47:29Z","title_canon_sha256":"7abe289b08f300daef5bf4c19f293de71f687e97d5c83f272fff1f99bf5a71a9"},"schema_version":"1.0","source":{"id":"2506.00654","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.00654","created_at":"2026-07-05T11:17:46Z"},{"alias_kind":"arxiv_version","alias_value":"2506.00654v1","created_at":"2026-07-05T11:17:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.00654","created_at":"2026-07-05T11:17:46Z"},{"alias_kind":"pith_short_12","alias_value":"YB4Q7OVMJWTN","created_at":"2026-07-05T11:17:46Z"},{"alias_kind":"pith_short_16","alias_value":"YB4Q7OVMJWTNT2NI","created_at":"2026-07-05T11:17:46Z"},{"alias_kind":"pith_short_8","alias_value":"YB4Q7OVM","created_at":"2026-07-05T11:17:46Z"}],"graph_snapshots":[{"event_id":"sha256:a31f83ee21ce2be00c270aa3e5505a4533e170f6712c836cf2797f6bb1ce9488","target":"graph","created_at":"2026-07-05T11:17:46Z","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/2506.00654/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Money laundering is a financial crime that poses a serious threat to financial integrity and social security. The growing number of transactions makes it necessary to use automatic tools that help law enforcement agencies detect such criminal activity. In this work, we present Amatriciana, a novel approach based on Graph Neural Networks to detect money launderers inside a graph of transactions by considering temporal information. Amatriciana uses the whole graph of transactions without splitting it into several time-based subgraphs, exploiting all relational information in the dataset. Our exp","authors_text":"Francesco Panebianco, Marco Di Gennaro, Marco Pianta, Michele Carminati, Stefano Zanero","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2025-05-31T17:47:29Z","title":"Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.00654","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:f2450eedcb2464120916af08ef7e2997852814cb0fe6753c5af0968b63fbb39d","target":"record","created_at":"2026-07-05T11:17:46Z","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":"73b96f6885e1e6ea4c6512374b286817c0a6926bd17982b61469997c66857781","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2025-05-31T17:47:29Z","title_canon_sha256":"7abe289b08f300daef5bf4c19f293de71f687e97d5c83f272fff1f99bf5a71a9"},"schema_version":"1.0","source":{"id":"2506.00654","kind":"arxiv","version":1}},"canonical_sha256":"c0790fbaac4da6d9e9a82c5333496fb927966f41b56d2b2f2fa4a6678bbe0f41","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c0790fbaac4da6d9e9a82c5333496fb927966f41b56d2b2f2fa4a6678bbe0f41","first_computed_at":"2026-07-05T11:17:46.607792Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:17:46.607792Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Jq5bChX7Sr/6YKWtE0ULg0zH9UGJlfzxAIGSKHRiqFiLgfj/dcppP1W9GT5racX8f3tq91Q2s4hK2bvvb8OXCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:17:46.608289Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.00654","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f2450eedcb2464120916af08ef7e2997852814cb0fe6753c5af0968b63fbb39d","sha256:a31f83ee21ce2be00c270aa3e5505a4533e170f6712c836cf2797f6bb1ce9488"],"state_sha256":"6718c871ade9572ac807ad9106c00cd5298af96e21e8b8349af51c78b8f9bf23"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AQRoFZBRFjFaK3wY1fiED507UZrL6z2WXUN6vuY/Z9A0aMsrfqXIZ3iUdLZ5N9yAWs5uZLskhSRoQFUZe5MUBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T23:54:21.386891Z","bundle_sha256":"ef5587a0b1da0e9cd19d59ef20a1dfc7c8b2d485f8ef278268905fa64a04280f"}}