{"as_of":"2026-08-07T10:07:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4b1bf6e618c97ce51d1cb954a40c0c69064c625edeb915085b0c70f5ad871d7c","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":1,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":1,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-23T23:39:40.979939Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-23T23:43:38.194563Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2310.05092","last_updated":"2023-10-08T09:41:18Z","snapshot_observed_at":"2026-08-02T10:57:16.685377Z","submitted_at":"2023-10-08T09:41:18Z","title":"Benchmarking Large Language Models with Augmented Instructions for Fine-grained Information Extraction","version":1},"cited_work":{"arxiv_id":"2310.05092","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.05092","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2310.05092 (2023)","venue":null,"work_id":"6aabc9a6-c50c-46a6-9413-b57bbf7a5cd4","year":2023},"citing_paper":{"arxiv_id":"2406.14075","last_updated":"2026-06-09T10:01:10Z","snapshot_observed_at":"2026-08-06T22:56:11.997903Z","submitted_at":"2024-06-20T07:50:37Z","title":"EXCEEDS: Extracting Complex Events via Nugget-based Grid Modeling in Scientific Domain","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-23T23:39:40.979939Z"},"links":{"cited_paper":"/paper/2310.05092","citing_paper":"/paper/2406.14075"},"observation_digest":"sha256:7ddc37ebd76f5e28f3196f289c6bb2804949027ee7d43727e649fccab51dc2d1","observation_id":"f1405b2f-3375-44fa-849d-f171579e20b4","resolution":{"observed_at":"2026-05-23T23:43:38.197639Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2310.05092/citation-record","integrity":"/paper/2310.05092/integrity","json":"/paper/2310.05092/citation-record.json","paper":"/paper/2310.05092"},"outbound":[],"paper":{"arxiv_id":"2310.05092","last_updated":"2023-10-08T09:41:18Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-02T10:57:16.685377Z","submitted_at":"2023-10-08T09:41:18Z","title":"Benchmarking Large Language Models with Augmented Instructions for Fine-grained Information Extraction"},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2310.05092."}