{"as_of":"2026-08-07T06:34:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:52e970c6df18c704012ec0b40f27396ea39917893c6d7300f6e051b86682acae","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":4,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":4,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T05:38:26.518075Z","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":"2026-07-03T10:37:56.491378Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2407.21057","last_updated":"2025-06-12T16:27:04Z","snapshot_observed_at":"2026-07-06T18:54:37.159782Z","submitted_at":"2024-07-25T02:59:52Z","title":"Multi-group Uncertainty Quantification for Long-form Text Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21057","snapshot_observed_at":"2026-08-07T05:38:26.518075Z","title":"and Wu, Z","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07461","last_updated":"2025-06-09T06:10:04Z","snapshot_observed_at":"2026-08-07T05:30:46.885126Z","submitted_at":"2025-06-09T06:10:04Z","title":"From Calibration to Collaboration: LLM Uncertainty Quantification Should Be More Human-Centered","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T05:38:26.518075Z"},"links":{"cited_paper":"/paper/2407.21057","citing_paper":"/paper/2506.07461"},"observation_digest":"sha256:f391a0e505eeae8393a75d702b0b3e50da474391d38e29839d03ec3cb9eb426a","observation_id":"f0b10dbb-6461-4bda-922b-802b466d79dc","resolution":{"observed_at":"2026-08-07T05:38:26.518075Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21057","last_updated":"2025-06-12T16:27:04Z","snapshot_observed_at":"2026-07-06T18:54:37.159782Z","submitted_at":"2024-07-25T02:59:52Z","title":"Multi-group Uncertainty Quantification for Long-form Text Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21057","snapshot_observed_at":"2026-08-02T22:16:19.693954Z","title":"14 Xin Liu, Muhammad Khalifa, and Lu Wang","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2602.17431","last_updated":"2026-06-22T12:49:00Z","snapshot_observed_at":"2026-08-02T22:16:16.983955Z","submitted_at":"2026-02-19T15:02:29Z","title":"Fine-Grained Uncertainty Quantification for Long-Form Language Model Outputs: A Comparative Study","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-02T22:16:19.693954Z"},"links":{"cited_paper":"/paper/2407.21057","citing_paper":"/paper/2602.17431"},"observation_digest":"sha256:d52ae9c8d83c6d8d1b0f68b945903a565df38d25b44df8b47d7bccfffd64974d","observation_id":"9dbccb37-645b-4d2d-93cc-6da88b279cc9","resolution":{"observed_at":"2026-08-02T22:16:19.693954Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21057","last_updated":"2025-06-12T16:27:04Z","snapshot_observed_at":"2026-07-06T18:54:37.159782Z","submitted_at":"2024-07-25T02:59:52Z","title":"Multi-group Uncertainty Quantification for Long-form Text Generation","version":2},"cited_work":{"arxiv_id":"2407.21057","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2407.21057","snapshot_observed_at":"2026-07-03T10:37:56.491378Z","title":null,"venue":null,"work_id":"560d08a5-47f9-4fca-a2de-793a19c1752b","year":null},"citing_paper":{"arxiv_id":"2606.12587","last_updated":"2026-06-10T18:34:36Z","snapshot_observed_at":"2026-07-06T23:51:27.152983Z","submitted_at":"2026-06-10T18:34:36Z","title":"Strategic Decision Support for AI Agents","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-06-27T09:57:46.960346Z"},"links":{"cited_paper":"/paper/2407.21057","citing_paper":"/paper/2606.12587"},"observation_digest":"sha256:44410059bf5642d1d58891423e21e033bf975f5d1c02d647e21d20ea03193bc6","observation_id":"e7d46812-b0df-4ea1-aa45-e98a3aa70052","resolution":{"observed_at":"2026-07-03T10:37:56.492944Z","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"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21057","last_updated":"2025-06-12T16:27:04Z","snapshot_observed_at":"2026-07-06T18:54:37.159782Z","submitted_at":"2024-07-25T02:59:52Z","title":"Multi-group Uncertainty Quantification for Long-form Text Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21057","snapshot_observed_at":"2026-08-01T20:16:16.264871Z","title":"Multi-group uncertainty quantification for long-form text genera- tion, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.16704","last_updated":"2026-07-18T08:38:19Z","snapshot_observed_at":"2026-08-06T13:09:59.892773Z","submitted_at":"2026-07-18T08:38:19Z","title":"Though Language Models Err While They Strive: Conformal Prediction for Self-Correcting Scientific Generation","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-01T20:16:16.264871Z"},"links":{"cited_paper":"/paper/2407.21057","citing_paper":"/paper/2607.16704"},"observation_digest":"sha256:ff9f471e7daaeec09ca68773186b2f6ae2a6176a7cc9a3d5bd3356944fa7e711","observation_id":"939c9be0-4d0a-4587-adb0-61c859baf372","resolution":{"observed_at":"2026-08-01T20:16:16.264871Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2407.21057/citation-record","integrity":"/paper/2407.21057/integrity","json":"/paper/2407.21057/citation-record.json","paper":"/paper/2407.21057"},"outbound":[],"paper":{"arxiv_id":"2407.21057","last_updated":"2025-06-12T16:27:04Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-06T18:54:37.159782Z","submitted_at":"2024-07-25T02:59:52Z","title":"Multi-group Uncertainty Quantification for Long-form Text Generation"},"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 4 inbound Pith citation observations for arXiv:2407.21057."}