{"as_of":"2026-08-09T08:12:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:7a84114a851334922fbd11843aa7fd1ba2e574df3948828687b7132d58525b60","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":"2026-08-02T05:32:58.523379Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2502.07786","last_updated":"2024-12-19T12:08:44Z","snapshot_observed_at":"2026-07-06T20:34:53.567141Z","submitted_at":"2024-12-19T12:08:44Z","title":"Counterexample Guided Program Repair Using Zero-Shot Learning and MaxSAT-based Fault Localization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.07786","snapshot_observed_at":"2026-07-13T21:57:39.418641Z","title":"com/index/gpt-5-system-card/","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2603.20334","last_updated":"2026-05-23T12:44:26Z","snapshot_observed_at":"2026-07-13T21:57:37.724988Z","submitted_at":"2026-03-20T08:16:15Z","title":"Procedural Refinement by LLM-driven Algorithmic Debugging for ARC-AGI-2","version":4},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-07-13T21:57:39.418641Z"},"links":{"cited_paper":"/paper/2502.07786","citing_paper":"/paper/2603.20334"},"observation_digest":"sha256:b424aab2d9b8b3d3b836aee88946fbcf2b64c20d720f3c87ae87a53034e855c5","observation_id":"ebac4fd6-939e-4316-b517-1c9d804ec4a7","resolution":{"observed_at":"2026-07-13T21:57:39.418641Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.07786","last_updated":"2024-12-19T12:08:44Z","snapshot_observed_at":"2026-07-06T20:34:53.567141Z","submitted_at":"2024-12-19T12:08:44Z","title":"Counterexample Guided Program Repair Using Zero-Shot Learning and MaxSAT-based Fault Localization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.07786","snapshot_observed_at":"2026-08-02T05:32:58.523379Z","title":"Orvalho, Mikoláš Janota, and Vasco Manquinho","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.14162","last_updated":"2026-07-14T23:56:44Z","snapshot_observed_at":"2026-08-08T10:14:34.469835Z","submitted_at":"2026-07-14T23:56:44Z","title":"Natural-Language to SysMLv2 Translation via Conformance-Driven Iterative Refinement","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-02T05:32:58.523379Z"},"links":{"cited_paper":"/paper/2502.07786","citing_paper":"/paper/2607.14162"},"observation_digest":"sha256:be28356a39284d5c594777db7e1a8c6246f5652821161c98e7c55d7e9c9e4f3b","observation_id":"b66be05d-a21c-48ec-924d-8be5aa4aa209","resolution":{"observed_at":"2026-08-02T05:32:58.523379Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2502.07786/citation-record","integrity":"/paper/2502.07786/integrity","json":"/paper/2502.07786/citation-record.json","paper":"/paper/2502.07786"},"outbound":[],"paper":{"arxiv_id":"2502.07786","last_updated":"2024-12-19T12:08:44Z","latest_version":1,"primary_category":"cs.SE","snapshot_observed_at":"2026-07-06T20:34:53.567141Z","submitted_at":"2024-12-19T12:08:44Z","title":"Counterexample Guided Program Repair Using Zero-Shot Learning and MaxSAT-based Fault Localization"},"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:2502.07786."}