{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:PJPLHGF2Y7B4MXP23PNJ2UDEQP","short_pith_number":"pith:PJPLHGF2","schema_version":"1.0","canonical_sha256":"7a5eb398bac7c3c65dfadbda9d506483c9cd99eaf181e2b512e286075bcd5f29","source":{"kind":"arxiv","id":"2508.14088","version":1},"attestation_state":"computed","paper":{"title":"CoBAD: Modeling Collective Behaviors for Human Mobility Anomaly Detection","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.SI"],"primary_cat":"cs.LG","authors_text":"Haomin Wen, Leman Akoglu, Shurui Cao","submitted_at":"2025-08-13T19:33:38Z","abstract_excerpt":"Detecting anomalies in human mobility is essential for applications such as public safety and urban planning. While traditional anomaly detection methods primarily focus on individual movement patterns (e.g., a child should stay at home at night), collective anomaly detection aims to identify irregularities in collective mobility behaviors across individuals (e.g., a child is at home alone while the parents are elsewhere) and remains an underexplored challenge. Unlike individual anomalies, collective anomalies require modeling spatiotemporal dependencies between individuals, introducing additi"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2508.14088","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-08-13T19:33:38Z","cross_cats_sorted":["cs.AI","cs.SI"],"title_canon_sha256":"a1df1a7860a57ade8c408ca99630dd10321794bc2bb71e6c48c0cb53002ce551","abstract_canon_sha256":"6fd51615484499072748b98e42ef26d9fc1cc798f82e452619829349a446f505"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:56:24.839040Z","signature_b64":"HAwYq6+uZ9k2uf4BDU7fqQrB5KUFdTyxm6JfYD8tW9CJjH1q+yygbeFbywpodV7WtIGVz9bnS7htVdn7LWd7DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7a5eb398bac7c3c65dfadbda9d506483c9cd99eaf181e2b512e286075bcd5f29","last_reissued_at":"2026-07-05T11:56:24.838652Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:56:24.838652Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"CoBAD: Modeling Collective Behaviors for Human Mobility Anomaly Detection","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.SI"],"primary_cat":"cs.LG","authors_text":"Haomin Wen, Leman Akoglu, Shurui Cao","submitted_at":"2025-08-13T19:33:38Z","abstract_excerpt":"Detecting anomalies in human mobility is essential for applications such as public safety and urban planning. While traditional anomaly detection methods primarily focus on individual movement patterns (e.g., a child should stay at home at night), collective anomaly detection aims to identify irregularities in collective mobility behaviors across individuals (e.g., a child is at home alone while the parents are elsewhere) and remains an underexplored challenge. Unlike individual anomalies, collective anomalies require modeling spatiotemporal dependencies between individuals, introducing additi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.14088","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/2508.14088/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2508.14088","created_at":"2026-07-05T11:56:24.838703+00:00"},{"alias_kind":"arxiv_version","alias_value":"2508.14088v1","created_at":"2026-07-05T11:56:24.838703+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.14088","created_at":"2026-07-05T11:56:24.838703+00:00"},{"alias_kind":"pith_short_12","alias_value":"PJPLHGF2Y7B4","created_at":"2026-07-05T11:56:24.838703+00:00"},{"alias_kind":"pith_short_16","alias_value":"PJPLHGF2Y7B4MXP2","created_at":"2026-07-05T11:56:24.838703+00:00"},{"alias_kind":"pith_short_8","alias_value":"PJPLHGF2","created_at":"2026-07-05T11:56:24.838703+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/PJPLHGF2Y7B4MXP23PNJ2UDEQP","json":"https://pith.science/pith/PJPLHGF2Y7B4MXP23PNJ2UDEQP.json","graph_json":"https://pith.science/api/pith-number/PJPLHGF2Y7B4MXP23PNJ2UDEQP/graph.json","events_json":"https://pith.science/api/pith-number/PJPLHGF2Y7B4MXP23PNJ2UDEQP/events.json","paper":"https://pith.science/paper/PJPLHGF2"},"agent_actions":{"view_html":"https://pith.science/pith/PJPLHGF2Y7B4MXP23PNJ2UDEQP","download_json":"https://pith.science/pith/PJPLHGF2Y7B4MXP23PNJ2UDEQP.json","view_paper":"https://pith.science/paper/PJPLHGF2","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2508.14088&json=true","fetch_graph":"https://pith.science/api/pith-number/PJPLHGF2Y7B4MXP23PNJ2UDEQP/graph.json","fetch_events":"https://pith.science/api/pith-number/PJPLHGF2Y7B4MXP23PNJ2UDEQP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/PJPLHGF2Y7B4MXP23PNJ2UDEQP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/PJPLHGF2Y7B4MXP23PNJ2UDEQP/action/storage_attestation","attest_author":"https://pith.science/pith/PJPLHGF2Y7B4MXP23PNJ2UDEQP/action/author_attestation","sign_citation":"https://pith.science/pith/PJPLHGF2Y7B4MXP23PNJ2UDEQP/action/citation_signature","submit_replication":"https://pith.science/pith/PJPLHGF2Y7B4MXP23PNJ2UDEQP/action/replication_record"}},"created_at":"2026-07-05T11:56:24.838703+00:00","updated_at":"2026-07-05T11:56:24.838703+00:00"}