{"as_of":"2026-08-08T08:23:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:fe41ddfc51bab5b71acc68b472f9a669fe7192f29d9d3a1e573100f68fbb9246","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":"2026-08-08T06:32:00.761636+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":"2026-08-06T18:53:31.453563Z","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":"2026-08-06T18:21:36.019089Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2403.18243","last_updated":"2024-03-27T04:20:18Z","snapshot_observed_at":"2026-07-06T17:51:44.212633Z","submitted_at":"2024-03-27T04:20:18Z","title":"Boosting Conversational Question Answering with Fine-Grained Retrieval-Augmentation and Self-Check","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.18243","snapshot_observed_at":"2026-08-06T18:53:31.453563Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.07030","last_updated":"2025-07-09T17:02:40Z","snapshot_observed_at":"2026-08-07T22:03:14.617539Z","submitted_at":"2025-07-09T17:02:40Z","title":"UniConv: Unifying Retrieval and Response Generation for Large Language Models in Conversations","version":1},"reference_index":65,"source":"arxiv_source","source_observed_at":"2026-08-06T18:53:31.453563Z"},"links":{"cited_paper":"/paper/2403.18243","citing_paper":"/paper/2507.07030"},"observation_digest":"sha256:fb074faf0346a806398c82cfec3520466fc52f717aa2a6147da0c587aba1870d","observation_id":"9dc7b0ee-22a9-4578-8655-c83cb11ce897","resolution":{"observed_at":"2026-08-06T18:53:31.453563Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.18243","last_updated":"2024-03-27T04:20:18Z","snapshot_observed_at":"2026-07-06T17:51:44.212633Z","submitted_at":"2024-03-27T04:20:18Z","title":"Boosting Conversational Question Answering with Fine-Grained Retrieval-Augmentation and Self-Check","version":1},"cited_work":{"arxiv_id":"2403.18243","doi":null,"metadata_source":"pith","pith_arxiv_id":"2403.18243","snapshot_observed_at":"2026-08-06T18:21:36.019089Z","title":"Boosting Conversational Question Answering with Fine-Grained Retrieval-Augmentation and Self-Check","venue":"cs.AI","work_id":"12c28200-8cc5-4315-94b0-c19146824fbb","year":2024},"citing_paper":{"arxiv_id":"2507.08603","last_updated":"2025-07-11T13:55:45Z","snapshot_observed_at":"2026-08-07T21:01:26.580728Z","submitted_at":"2025-07-11T13:55:45Z","title":"Unlocking Speech Instruction Data Potential with Query Rewriting","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-06T18:21:35.616120Z"},"links":{"cited_paper":"/paper/2403.18243","citing_paper":"/paper/2507.08603"},"observation_digest":"sha256:185b452498736905a97b43ccb3762facbb6ffbfcbe0d56faa450900d41330fa8","observation_id":"caf75ea3-bdf1-4e3a-8baa-3959a97ba84a","resolution":{"observed_at":"2026-08-06T18:21:36.125549Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2403.18243/citation-record","integrity":"/paper/2403.18243/integrity","json":"/paper/2403.18243/citation-record.json","paper":"/paper/2403.18243"},"outbound":[],"paper":{"arxiv_id":"2403.18243","last_updated":"2024-03-27T04:20:18Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-07-06T17:51:44.212633Z","submitted_at":"2024-03-27T04:20:18Z","title":"Boosting Conversational Question Answering with Fine-Grained Retrieval-Augmentation and Self-Check"},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2403.18243."}