{"as_of":"2026-08-07T03:26:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ca59ab2c2bc6c36b02947e1cb1ddd4bfb5510653a7d1ec0ce09fc070821d664e","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":"2026-08-06T06:34:29.942622+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":"2026-05-20T08:37:41.455802Z","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":"2026-05-20T08:38:10.323125Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2412.07412","last_updated":"2024-12-10T11:05:26Z","snapshot_observed_at":"2026-07-06T20:04:34.632244Z","submitted_at":"2024-12-10T11:05:26Z","title":"Generating Knowledge Graphs from Large Language Models: A Comparative Study of GPT-4, LLaMA 2, and BERT","version":1},"cited_work":{"arxiv_id":"2412.07412","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.07412","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2412.07412 , year=","venue":null,"work_id":"feb406fd-efbc-4ed5-b9eb-591f949dcaec","year":null},"citing_paper":{"arxiv_id":"2605.19174","last_updated":"2026-05-27T17:23:36Z","snapshot_observed_at":"2026-08-05T07:40:37.486071Z","submitted_at":"2026-05-18T22:56:11Z","title":"Restructure This: Using AI to Restructure Onboarding Documents to Reduce Cognitive Overload","version":1},"reference_index":107,"source":"arxiv_source","source_observed_at":"2026-05-20T08:37:41.455802Z"},"links":{"cited_paper":"/paper/2412.07412","citing_paper":"/paper/2605.19174"},"observation_digest":"sha256:75f03a05f65aa509f21ee2cc43a4f17a4d7749e12e731058feff52daa06414e0","observation_id":"173f469e-83c1-4775-aebb-5203ab507c28","resolution":{"observed_at":"2026-05-20T08:38:10.325613Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2412.07412/citation-record","integrity":"/paper/2412.07412/integrity","json":"/paper/2412.07412/citation-record.json","paper":"/paper/2412.07412"},"outbound":[],"paper":{"arxiv_id":"2412.07412","last_updated":"2024-12-10T11:05:26Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-06T20:04:34.632244Z","submitted_at":"2024-12-10T11:05:26Z","title":"Generating Knowledge Graphs from Large Language Models: A Comparative Study of GPT-4, LLaMA 2, and BERT"},"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":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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:2412.07412."}