{"as_of":"2026-08-10T05:10:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1420689d199eee946a96b900b2ce141f1ff69696d1c4b5ec98ab0875508e2dba","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":3,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":3,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T15:31:44.948205Z","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":"2026-08-07T00:14:10.025866Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2402.14116","last_updated":"2024-06-06T16:41:21Z","snapshot_observed_at":"2026-08-05T07:14:49.201751Z","submitted_at":"2024-02-21T20:30:45Z","title":"FanOutQA: A Multi-Hop, Multi-Document Question Answering Benchmark for Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.14116","snapshot_observed_at":"2026-08-07T12:04:27.522421Z","title":"FanOutQA: A multi-hop, multi-document question answering benchmark for large language models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.00664","last_updated":"2025-05-31T18:33:39Z","snapshot_observed_at":"2026-08-09T19:56:09.245369Z","submitted_at":"2025-05-31T18:33:39Z","title":"OntoRAG: Enhancing Question-Answering through Automated Ontology Derivation from Unstructured Knowledge Bases","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T12:04:27.522421Z"},"links":{"cited_paper":"/paper/2402.14116","citing_paper":"/paper/2506.00664"},"observation_digest":"sha256:404d6de466353407aadece8c654e390e819089ebc70a53f4b8c1e04068755418","observation_id":"f2bce787-233f-4591-a1fd-85ff6e96e49d","resolution":{"observed_at":"2026-08-07T12:04:27.522421Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.14116","last_updated":"2024-06-06T16:41:21Z","snapshot_observed_at":"2026-08-05T07:14:49.201751Z","submitted_at":"2024-02-21T20:30:45Z","title":"FanOutQA: A Multi-Hop, Multi-Document Question Answering Benchmark for Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.14116","snapshot_observed_at":"2026-08-07T15:31:44.948205Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.02000","last_updated":"2025-06-23T01:41:05Z","snapshot_observed_at":"2026-08-07T15:25:33.498661Z","submitted_at":"2025-05-20T20:54:37Z","title":"NovelHopQA: Diagnosing Multi-Hop Reasoning Failures in Long Narrative Contexts","version":2},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-07T15:31:44.948205Z"},"links":{"cited_paper":"/paper/2402.14116","citing_paper":"/paper/2506.02000"},"observation_digest":"sha256:cc982a4fb3264cf7ba9f77677b92a06de76f3f41521be65fb051277beb7f46ee","observation_id":"9019518f-0e40-4776-96d6-5b58b9a00648","resolution":{"observed_at":"2026-08-07T15:31:44.948205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.14116","last_updated":"2024-06-06T16:41:21Z","snapshot_observed_at":"2026-08-05T07:14:49.201751Z","submitted_at":"2024-02-21T20:30:45Z","title":"FanOutQA: A Multi-Hop, Multi-Document Question Answering Benchmark for Large Language Models","version":2},"cited_work":{"arxiv_id":"2402.14116","doi":null,"metadata_source":"pith","pith_arxiv_id":"2402.14116","snapshot_observed_at":"2026-08-07T00:14:10.025866Z","title":"FanOutQA: A Multi-Hop, Multi-Document Question Answering Benchmark for Large Language Models","venue":"cs.CL","work_id":"2f082353-2bd7-4e0e-a62d-2375250c05c6","year":2024},"citing_paper":{"arxiv_id":"2506.14927","last_updated":"2025-06-17T19:14:30Z","snapshot_observed_at":"2026-08-09T13:20:44.500546Z","submitted_at":"2025-06-17T19:14:30Z","title":"MDBench: A Synthetic Multi-Document Reasoning Benchmark Generated with Knowledge Guidance","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-07T00:14:09.575548Z"},"links":{"cited_paper":"/paper/2402.14116","citing_paper":"/paper/2506.14927"},"observation_digest":"sha256:369fb2079494d22c480ea34c74860a3a07b721a67983638a0810211896e372a2","observation_id":"e5e4a797-0d26-4906-9fe7-574979813495","resolution":{"observed_at":"2026-08-07T00:14:10.137075Z","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"}}],"links":{"evidence":"/evidence","html":"/paper/2402.14116/citation-record","integrity":"/paper/2402.14116/integrity","json":"/paper/2402.14116/citation-record.json","paper":"/paper/2402.14116"},"outbound":[],"paper":{"arxiv_id":"2402.14116","last_updated":"2024-06-06T16:41:21Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-05T07:14:49.201751Z","submitted_at":"2024-02-21T20:30:45Z","title":"FanOutQA: A Multi-Hop, Multi-Document Question Answering Benchmark for Large Language Models"},"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 3 inbound Pith citation observations for arXiv:2402.14116."}