{"schema":"https://pith.science/schemas/pith-integrity/v1.json","pith_number":"2604.27714","arxiv_id":"2604.27714","integrity":{"available":true,"endpoint":"/pith/2604.27714/integrity.json","summary":{"critical":3,"advisory":0,"informational":0,"by_detector":{"doi_compliance":{"total":3,"critical":3,"advisory":0,"informational":0}}},"clean":false,"detectors_run":[{"name":"ai_meta_artifact","version":"1.0.0","status":"completed","ran_at":"2026-05-20T21:40:19.925603Z","findings_count":0},{"name":"doi_compliance","version":"1.0.0","status":"completed","ran_at":"2026-05-19T18:56:11.980163Z","findings_count":3}],"findings":[{"detector":"doi_compliance","finding_type":"unresolvable_identifier","severity":"critical","verdict_class":"cross_source","note":"Identifier '10.5555/3454287.3455202' is syntactically valid but the DOI registry (doi.org) returned 404, and Crossref / OpenAlex / internal corpus also have no record. The cited work could not be located through any authoritative source.","detected_doi":"10.5555/3454287.3455202","detected_arxiv_id":null,"ref_index":20,"audited_at":"2026-05-19T18:56:11.980163Z"},{"detector":"doi_compliance","finding_type":"unresolvable_identifier","severity":"critical","verdict_class":"cross_source","note":"Identifier '10.18653/v1/2024.lrec-main.1494' is syntactically valid but the DOI registry (doi.org) returned 404, and Crossref / OpenAlex / internal corpus also have no record. The cited work could not be located through any authoritative source.","detected_doi":"10.18653/v1/2024.lrec-main.1494","detected_arxiv_id":null,"ref_index":13,"audited_at":"2026-05-19T18:56:11.980163Z"},{"detector":"doi_compliance","finding_type":"unresolvable_identifier","severity":"critical","verdict_class":"cross_source","note":"Identifier '10.5555/3620237.3620604' is syntactically valid but the DOI registry (doi.org) returned 404, and Crossref / OpenAlex / internal corpus also have no record. The cited work could not be located through any authoritative source.","detected_doi":"10.5555/3620237.3620604","detected_arxiv_id":null,"ref_index":16,"audited_at":"2026-05-19T18:56:11.980163Z"}],"snapshot_sha256":"80599af661d0ecebebbf6468c5e123e16f166d1dd8cf566f0906d058e3b6c3d1"},"events":[{"event_id":2637,"event_type":"pith.integrity.v1","payload_sha256":"4971a7502633362fce01029ff15e87fa6c03ebec369efb7987cdb69db8e2be89","signature_b64":"GmMzbAsn4OE3ShUV65Vd/w0brrdQZndYeFvfD8MmQ/BUVV+QFXJRHADRFHgwubTBXUdo1y3mrmp/JfFAaIEPBQ==","signing_key_id":"pith-v1-2026-05","created_at":"2026-05-19T18:57:18.616861+00:00","payload":{"note":"Identifier '10.5555/3454287.3455202' is syntactically valid but the DOI registry (doi.org) returned 404, and Crossref / OpenAlex / internal corpus also have no record. The cited work could not be located through any authoritative source.","snippet":"Yaqin Zhou, Shangqing Liu, Jingkai Siow, Xiaoning Du, and Yang Liu. 2019. Devign: Effective Vulnerability Identification by Learning Comprehensive Pro- gram Semantics via Graph Neural Networks. InAdvances in Neural Information Processing Sy","arxiv_id":"2604.27714","detector":"doi_compliance","evidence":{"doi":"10.5555/3454287.3455202","arxiv_id":null,"ref_index":20,"raw_excerpt":"Yaqin Zhou, Shangqing Liu, Jingkai Siow, Xiaoning Du, and Yang Liu. 2019. Devign: Effective Vulnerability Identification by Learning Comprehensive Pro- gram Semantics via Graph Neural Networks. InAdvances in Neural Information Processing Systems, Vol. 32. doi:10.5555/3454287.3455202","verdict_class":"cross_source","checked_sources":["crossref_by_doi","openalex_by_doi","doi_org_head"]},"severity":"critical","ref_index":20,"audited_at":"2026-05-19T18:56:11.980163Z","event_type":"pith.integrity.v1","detected_doi":"10.5555/3454287.3455202","detector_url":"https://pith.science/pith-integrity-protocol#doi_compliance","external_url":null,"finding_type":"unresolvable_identifier","evidence_hash":"a9f773e94154a45f8b0c9ff7febb0e5b6b35a40387e665c6894ea79586b8d183","paper_version":1,"verdict_class":"cross_source","resolved_title":null,"detector_version":"1.0.0","detected_arxiv_id":null}},{"event_id":2636,"event_type":"pith.integrity.v1","payload_sha256":"f56549b894d276349d204fce7e0d7e11d4db6d3c7e1d781b1534d7636676d5aa","signature_b64":"WZUucHAxTkay30py+TAaiZ6JkINPCPN1PKQqMre6fTCjyPyykbIHpwB0nTt8oUthhfO4OTiDPv1+0OHunkIGDA==","signing_key_id":"pith-v1-2026-05","created_at":"2026-05-19T18:57:18.615841+00:00","payload":{"note":"Identifier '10.5555/3620237.3620604' is syntactically valid but the DOI registry (doi.org) returned 404, and Crossref / OpenAlex / internal corpus also have no record. The cited work could not be located through any authoritative source.","snippet":"Yisroel Mirsky, George Macon, Michael Brown, Carter Yagemann, Matthew Pruett, Evan Downing, Sukarno Mertoguno, and Wenke Lee. 2023. VulChecker: Graph-based Vulnerability Localization in Source Code. In32nd USENIX Security Symposium. 2041–20","arxiv_id":"2604.27714","detector":"doi_compliance","evidence":{"doi":"10.5555/3620237.3620604","arxiv_id":null,"ref_index":16,"raw_excerpt":"Yisroel Mirsky, George Macon, Michael Brown, Carter Yagemann, Matthew Pruett, Evan Downing, Sukarno Mertoguno, and Wenke Lee. 2023. VulChecker: Graph-based Vulnerability Localization in Source Code. In32nd USENIX Security Symposium. 2041–2058. doi:10.5555/3620237.3620604","verdict_class":"cross_source","checked_sources":["crossref_by_doi","openalex_by_doi","doi_org_head"]},"severity":"critical","ref_index":16,"audited_at":"2026-05-19T18:56:11.980163Z","event_type":"pith.integrity.v1","detected_doi":"10.5555/3620237.3620604","detector_url":"https://pith.science/pith-integrity-protocol#doi_compliance","external_url":null,"finding_type":"unresolvable_identifier","evidence_hash":"111d229317ad6273cd78b35450d8a75dcc672b3236a52682a5049d5ddb2ae9f1","paper_version":1,"verdict_class":"cross_source","resolved_title":null,"detector_version":"1.0.0","detected_arxiv_id":null}},{"event_id":2635,"event_type":"pith.integrity.v1","payload_sha256":"cbaacc92fd52fb2d898c1aebc047fe49d2090e069c38fd69454e261904b1d0e5","signature_b64":"r5cbpQb4fzrN0u2A2ZZGTLrPbAPKVEPbkLJuiS3KJGRvxSr/0FQEJj7QHFao2DVPPRH8bY5uk5g6VzfG/FAyAg==","signing_key_id":"pith-v1-2026-05","created_at":"2026-05-19T18:57:18.614703+00:00","payload":{"note":"Identifier '10.18653/v1/2024.lrec-main.1494' is syntactically valid but the DOI registry (doi.org) returned 404, and Crossref / OpenAlex / internal corpus also have no record. The cited work could not be located through any authoritative source.","snippet":"Zhiming Li, Yanzhou Li, Tianlin Li, Mengnan Du, Bozhi Wu, Yushi Cao, Junzhe Jiang, and Yang Liu. 2024. Unveiling Project-Specific Bias in Neural Code Models. InProceedings of the 2024 Joint International Conference on Computational Lin- gui","arxiv_id":"2604.27714","detector":"doi_compliance","evidence":{"doi":"10.18653/v1/2024.lrec-main.1494","arxiv_id":null,"ref_index":13,"raw_excerpt":"Zhiming Li, Yanzhou Li, Tianlin Li, Mengnan Du, Bozhi Wu, Yushi Cao, Junzhe Jiang, and Yang Liu. 2024. Unveiling Project-Specific Bias in Neural Code Models. InProceedings of the 2024 Joint International Conference on Computational Lin- guistics, Language Resources and Evaluation (LREC-COLING 2024). 17205–17216. doi:10.18653/v1/2024.lrec-main.1494","verdict_class":"cross_source","checked_sources":["crossref_by_doi","openalex_by_doi","doi_org_head"]},"severity":"critical","ref_index":13,"audited_at":"2026-05-19T18:56:11.980163Z","event_type":"pith.integrity.v1","detected_doi":"10.18653/v1/2024.lrec-main.1494","detector_url":"https://pith.science/pith-integrity-protocol#doi_compliance","external_url":null,"finding_type":"unresolvable_identifier","evidence_hash":"3b0efcc76dc20d81d580f884ef7621ad5fb4fb73e7758f391659a12ace8ca962","paper_version":1,"verdict_class":"cross_source","resolved_title":null,"detector_version":"1.0.0","detected_arxiv_id":null}}],"endpoint_self":"/pith/2604.27714/integrity.json","protocol_url":"https://pith.science/pith-integrity-protocol"}