{"as_of":"2026-08-09T20:01:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0e598d8fe83b2543ea19e8f8caa86535ff57702c2df6c22fd20ba60a228877a5","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":2,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":2,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T04:36:47.616477Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-07T04:36:50.944476Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2309.14677","last_updated":"2023-09-26T05:05:34Z","snapshot_observed_at":"2026-07-06T16:23:41.780696Z","submitted_at":"2023-09-26T05:05:34Z","title":"XGV-BERT: Leveraging Contextualized Language Model and Graph Neural Network for Efficient Software Vulnerability Detection","version":1},"cited_work":{"arxiv_id":"2309.14677","doi":null,"metadata_source":"pith","pith_arxiv_id":"2309.14677","snapshot_observed_at":"2026-08-07T04:36:50.944476Z","title":"XGV-BERT: Leveraging Contextualized Language Model and Graph Neural Network for Efficient Software Vulnerability Detection","venue":"cs.CR","work_id":"1214976c-47db-4960-904c-d31ff012a4a9","year":2023},"citing_paper":{"arxiv_id":"2506.10280","last_updated":"2025-06-12T01:42:38Z","snapshot_observed_at":"2026-08-08T20:10:44.047893Z","submitted_at":"2025-06-12T01:42:38Z","title":"AI-Based Software Vulnerability Detection: A Systematic Literature Review","version":1},"reference_index":108,"source":"pdf_text","source_observed_at":"2026-08-07T04:36:47.616477Z"},"links":{"cited_paper":"/paper/2309.14677","citing_paper":"/paper/2506.10280"},"observation_digest":"sha256:a26a413259b3ff481efe34697e27aba769d325143262e51f21ceb37485dee606","observation_id":"032591b8-daa1-4616-838a-fbf4dbdc6a03","resolution":{"observed_at":"2026-08-07T04:36:50.949932Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.14677","last_updated":"2023-09-26T05:05:34Z","snapshot_observed_at":"2026-07-06T16:23:41.780696Z","submitted_at":"2023-09-26T05:05:34Z","title":"XGV-BERT: Leveraging Contextualized Language Model and Graph Neural Network for Efficient Software Vulnerability Detection","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.14677","snapshot_observed_at":"2026-08-06T16:24:28.672841Z","title":"Xgv-bert: Leveraging contextualized language model and graph neural network for efficient software vulnerability detection,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.13629","last_updated":"2025-07-18T03:41:18Z","snapshot_observed_at":"2026-08-07T10:03:57.005879Z","submitted_at":"2025-07-18T03:41:18Z","title":"Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-06T16:24:28.672841Z"},"links":{"cited_paper":"/paper/2309.14677","citing_paper":"/paper/2507.13629"},"observation_digest":"sha256:8892794c791765667d4442dde1330565c8370658628e8e3f784e2a2b80bfa228","observation_id":"f84ed160-da98-44a3-a45e-ffd34583f64d","resolution":{"observed_at":"2026-08-06T16:24:28.672841Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2309.14677/citation-record","integrity":"/paper/2309.14677/integrity","json":"/paper/2309.14677/citation-record.json","paper":"/paper/2309.14677"},"outbound":[],"paper":{"arxiv_id":"2309.14677","last_updated":"2023-09-26T05:05:34Z","latest_version":1,"primary_category":"cs.CR","snapshot_observed_at":"2026-07-06T16:23:41.780696Z","submitted_at":"2023-09-26T05:05:34Z","title":"XGV-BERT: Leveraging Contextualized Language Model and Graph Neural Network for Efficient Software Vulnerability Detection"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2309.14677."}