{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:V6E3V32OMLJOC2W37NAIMMK6XH","short_pith_number":"pith:V6E3V32O","schema_version":"1.0","canonical_sha256":"af89baef4e62d2e16adbfb4086315eb9db648f3abd66540e50809355e6158e83","source":{"kind":"arxiv","id":"2506.02617","version":1},"attestation_state":"computed","paper":{"title":"Toward Understanding Bugs in Vector Database Management Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SE","authors_text":"Haoyu Wang, Kai Chen, Shenao Wang, Xinyi Hou, Yanjie Zhao, Yinglin Xie","submitted_at":"2025-06-03T08:34:01Z","abstract_excerpt":"Vector database management systems (VDBMSs) play a crucial role in facilitating semantic similarity searches over high-dimensional embeddings from diverse data sources. While VDBMSs are widely used in applications such as recommendation, retrieval-augmented generation (RAG), and multimodal search, their reliability remains underexplored. Traditional database reliability models cannot be directly applied to VDBMSs because of fundamental differences in data representation, query mechanisms, and system architecture. To address this gap, we present the first large-scale empirical study of software"},"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":"2506.02617","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2025-06-03T08:34:01Z","cross_cats_sorted":[],"title_canon_sha256":"0551b96962c9bdc8e8492650eb58bb328ae8bf1c1eab033f7f3162e13612fdd4","abstract_canon_sha256":"ecd0fd8045df5bf7bdd3a3aef5ba4f2fe465689d9ad9a5fcca1f4206087d8e4e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:15:05.458814Z","signature_b64":"yooACdp/BOTHeYGwEDph7cjGpKMZVws/77fOB2b05pao7YUrA57uohtJVewzksclefHyDUsR5C7pqqSsE5uiBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"af89baef4e62d2e16adbfb4086315eb9db648f3abd66540e50809355e6158e83","last_reissued_at":"2026-07-05T11:15:05.458326Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:15:05.458326Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Toward Understanding Bugs in Vector Database Management Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SE","authors_text":"Haoyu Wang, Kai Chen, Shenao Wang, Xinyi Hou, Yanjie Zhao, Yinglin Xie","submitted_at":"2025-06-03T08:34:01Z","abstract_excerpt":"Vector database management systems (VDBMSs) play a crucial role in facilitating semantic similarity searches over high-dimensional embeddings from diverse data sources. While VDBMSs are widely used in applications such as recommendation, retrieval-augmented generation (RAG), and multimodal search, their reliability remains underexplored. Traditional database reliability models cannot be directly applied to VDBMSs because of fundamental differences in data representation, query mechanisms, and system architecture. To address this gap, we present the first large-scale empirical study of software"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.02617","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/2506.02617/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":"2506.02617","created_at":"2026-07-05T11:15:05.458386+00:00"},{"alias_kind":"arxiv_version","alias_value":"2506.02617v1","created_at":"2026-07-05T11:15:05.458386+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.02617","created_at":"2026-07-05T11:15:05.458386+00:00"},{"alias_kind":"pith_short_12","alias_value":"V6E3V32OMLJO","created_at":"2026-07-05T11:15:05.458386+00:00"},{"alias_kind":"pith_short_16","alias_value":"V6E3V32OMLJOC2W3","created_at":"2026-07-05T11:15:05.458386+00:00"},{"alias_kind":"pith_short_8","alias_value":"V6E3V32O","created_at":"2026-07-05T11:15:05.458386+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/V6E3V32OMLJOC2W37NAIMMK6XH","json":"https://pith.science/pith/V6E3V32OMLJOC2W37NAIMMK6XH.json","graph_json":"https://pith.science/api/pith-number/V6E3V32OMLJOC2W37NAIMMK6XH/graph.json","events_json":"https://pith.science/api/pith-number/V6E3V32OMLJOC2W37NAIMMK6XH/events.json","paper":"https://pith.science/paper/V6E3V32O"},"agent_actions":{"view_html":"https://pith.science/pith/V6E3V32OMLJOC2W37NAIMMK6XH","download_json":"https://pith.science/pith/V6E3V32OMLJOC2W37NAIMMK6XH.json","view_paper":"https://pith.science/paper/V6E3V32O","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2506.02617&json=true","fetch_graph":"https://pith.science/api/pith-number/V6E3V32OMLJOC2W37NAIMMK6XH/graph.json","fetch_events":"https://pith.science/api/pith-number/V6E3V32OMLJOC2W37NAIMMK6XH/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/V6E3V32OMLJOC2W37NAIMMK6XH/action/timestamp_anchor","attest_storage":"https://pith.science/pith/V6E3V32OMLJOC2W37NAIMMK6XH/action/storage_attestation","attest_author":"https://pith.science/pith/V6E3V32OMLJOC2W37NAIMMK6XH/action/author_attestation","sign_citation":"https://pith.science/pith/V6E3V32OMLJOC2W37NAIMMK6XH/action/citation_signature","submit_replication":"https://pith.science/pith/V6E3V32OMLJOC2W37NAIMMK6XH/action/replication_record"}},"created_at":"2026-07-05T11:15:05.458386+00:00","updated_at":"2026-07-05T11:15:05.458386+00:00"}