{"as_of":"2026-08-10T04:54:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:6a4e4ed599201e7d78ac7debb675eb0846d7eb364e5a2f4326bd2ddeefdc41ce","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":"2026-08-07T15:02:18.371991Z","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":"2026-08-07T15:02:26.319191Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2503.20263","last_updated":"2025-03-26T06:09:55Z","snapshot_observed_at":"2026-08-07T16:36:30.468136Z","submitted_at":"2025-03-26T06:09:55Z","title":"L4: Diagnosing Large-scale LLM Training Failures via Automated Log Analysis","version":1},"cited_work":{"arxiv_id":"2503.20263","doi":null,"metadata_source":"pith","pith_arxiv_id":"2503.20263","snapshot_observed_at":"2026-08-07T15:02:26.319191Z","title":"L4: Diagnosing Large-scale LLM Training Failures via Automated Log Analysis","venue":"cs.SE","work_id":"ab825cbb-499d-4229-a337-89954f282ed8","year":2025},"citing_paper":{"arxiv_id":"2505.16590","last_updated":"2025-09-04T04:06:40Z","snapshot_observed_at":"2026-08-09T22:50:30.971581Z","submitted_at":"2025-05-22T12:26:53Z","title":"Larger Is Not Always Better: Exploring Small Open-source Language Models in Logging Statement Generation","version":3},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T15:02:18.371991Z"},"links":{"cited_paper":"/paper/2503.20263","citing_paper":"/paper/2505.16590"},"observation_digest":"sha256:65360fa465b1119a8ed4610d2ca1fa3ed5c6266af2c154ac2bb6ed4879a7795a","observation_id":"88f36398-213c-48cf-a042-fe1d11b587cb","resolution":{"observed_at":"2026-08-07T15:02:26.372421Z","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":"2503.20263","last_updated":"2025-03-26T06:09:55Z","snapshot_observed_at":"2026-08-07T16:36:30.468136Z","submitted_at":"2025-03-26T06:09:55Z","title":"L4: Diagnosing Large-scale LLM Training Failures via Automated Log Analysis","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.20263","snapshot_observed_at":"2026-07-13T21:22:51.148626Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2603.20617","last_updated":"2026-06-03T22:09:35Z","snapshot_observed_at":"2026-08-03T09:44:31.835764Z","submitted_at":"2026-03-21T03:25:10Z","title":"The AI Layoff Trap","version":3},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-07-13T21:22:51.148626Z"},"links":{"cited_paper":"/paper/2503.20263","citing_paper":"/paper/2603.20617"},"observation_digest":"sha256:5fb897cd3dd8dcd0eb04e38c42a33f5d72888c5a8de1106a36e1920407170d9b","observation_id":"292f1f2d-929a-4a85-b70f-8ecf191e569c","resolution":{"observed_at":"2026-07-13T21:22:51.148626Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2503.20263/citation-record","integrity":"/paper/2503.20263/integrity","json":"/paper/2503.20263/citation-record.json","paper":"/paper/2503.20263"},"outbound":[],"paper":{"arxiv_id":"2503.20263","last_updated":"2025-03-26T06:09:55Z","latest_version":1,"primary_category":"cs.SE","snapshot_observed_at":"2026-08-07T16:36:30.468136Z","submitted_at":"2025-03-26T06:09:55Z","title":"L4: Diagnosing Large-scale LLM Training Failures via Automated Log Analysis"},"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 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2503.20263."}