{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:RWLFDV6TRQGMYKUVKZ6SPSFU2X","short_pith_number":"pith:RWLFDV6T","schema_version":"1.0","canonical_sha256":"8d9651d7d38c0ccc2a95567d27c8b4d5c27462a52f9966fe49a625e6ba784fa6","source":{"kind":"arxiv","id":"2605.26068","version":1},"attestation_state":"computed","paper":{"title":"Rethinking Weak Supervision in Anomaly Detection: A Comprehensive Benchmark","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Chaochuan Hou, Hailiang Huang, Minqi Jiang, Shiping Wang, Shuang Liang, Siyuan Zhou, Songqiao Han, Wu Zhenbo, Xu Yao","submitted_at":"2026-05-25T17:32:58Z","abstract_excerpt":"Weakly supervised anomaly detection (WSAD) has developed in three primary directions: incomplete, inexact, and inaccurate supervision. However, these directions remain isolated, lacking a unified framework to assess whether they address unique challenges or share fundamental mechanics. This paper introduces WSADBench, the first benchmark that unifies evaluation across distinct weakly supervised scenarios, benchmarking diverse approaches from specialized WSAD methods to advanced tabular foundation models. WSADBench establishes standardized protocols to evaluate 36 algorithms across 4 modalities"},"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":"2605.26068","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-25T17:32:58Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"559e2c31f8c5b98e1bd5094c770983aa0fde641a0d4a84a46d2083b0835c897d","abstract_canon_sha256":"e99d2de966f861f6ce03d89f05897fb10d6178907ffa34557010d3856233c972"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-26T02:05:25.644747Z","signature_b64":"x+bYPUsQShQSMDgjkCKvD3ePdg7otqx2DM0OJYyRry70ZwxlRP0npi3OHoCkB/DgBYK9db2UKRKs1o9An3BmCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8d9651d7d38c0ccc2a95567d27c8b4d5c27462a52f9966fe49a625e6ba784fa6","last_reissued_at":"2026-05-26T02:05:25.644016Z","signature_status":"signed_v1","first_computed_at":"2026-05-26T02:05:25.644016Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Rethinking Weak Supervision in Anomaly Detection: A Comprehensive Benchmark","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Chaochuan Hou, Hailiang Huang, Minqi Jiang, Shiping Wang, Shuang Liang, Siyuan Zhou, Songqiao Han, Wu Zhenbo, Xu Yao","submitted_at":"2026-05-25T17:32:58Z","abstract_excerpt":"Weakly supervised anomaly detection (WSAD) has developed in three primary directions: incomplete, inexact, and inaccurate supervision. However, these directions remain isolated, lacking a unified framework to assess whether they address unique challenges or share fundamental mechanics. This paper introduces WSADBench, the first benchmark that unifies evaluation across distinct weakly supervised scenarios, benchmarking diverse approaches from specialized WSAD methods to advanced tabular foundation models. WSADBench establishes standardized protocols to evaluate 36 algorithms across 4 modalities"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.26068","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/2605.26068/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":"2605.26068","created_at":"2026-05-26T02:05:25.644130+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.26068v1","created_at":"2026-05-26T02:05:25.644130+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.26068","created_at":"2026-05-26T02:05:25.644130+00:00"},{"alias_kind":"pith_short_12","alias_value":"RWLFDV6TRQGM","created_at":"2026-05-26T02:05:25.644130+00:00"},{"alias_kind":"pith_short_16","alias_value":"RWLFDV6TRQGMYKUV","created_at":"2026-05-26T02:05:25.644130+00:00"},{"alias_kind":"pith_short_8","alias_value":"RWLFDV6T","created_at":"2026-05-26T02:05:25.644130+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/RWLFDV6TRQGMYKUVKZ6SPSFU2X","json":"https://pith.science/pith/RWLFDV6TRQGMYKUVKZ6SPSFU2X.json","graph_json":"https://pith.science/api/pith-number/RWLFDV6TRQGMYKUVKZ6SPSFU2X/graph.json","events_json":"https://pith.science/api/pith-number/RWLFDV6TRQGMYKUVKZ6SPSFU2X/events.json","paper":"https://pith.science/paper/RWLFDV6T"},"agent_actions":{"view_html":"https://pith.science/pith/RWLFDV6TRQGMYKUVKZ6SPSFU2X","download_json":"https://pith.science/pith/RWLFDV6TRQGMYKUVKZ6SPSFU2X.json","view_paper":"https://pith.science/paper/RWLFDV6T","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.26068&json=true","fetch_graph":"https://pith.science/api/pith-number/RWLFDV6TRQGMYKUVKZ6SPSFU2X/graph.json","fetch_events":"https://pith.science/api/pith-number/RWLFDV6TRQGMYKUVKZ6SPSFU2X/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RWLFDV6TRQGMYKUVKZ6SPSFU2X/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RWLFDV6TRQGMYKUVKZ6SPSFU2X/action/storage_attestation","attest_author":"https://pith.science/pith/RWLFDV6TRQGMYKUVKZ6SPSFU2X/action/author_attestation","sign_citation":"https://pith.science/pith/RWLFDV6TRQGMYKUVKZ6SPSFU2X/action/citation_signature","submit_replication":"https://pith.science/pith/RWLFDV6TRQGMYKUVKZ6SPSFU2X/action/replication_record"}},"created_at":"2026-05-26T02:05:25.644130+00:00","updated_at":"2026-05-26T02:05:25.644130+00:00"}