{"as_of":"2026-08-09T08:59:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2cd2c8ddcb61bcd8be9a6158b59f7f0a53f8f8ea03d75063f6e859404251b375","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":"2026-08-09T06:31:02.800959+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":"2026-08-04T17:03:13.046521Z","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":"2026-05-21T10:54:07.890776Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2410.22971","last_updated":"2024-10-30T12:38:49Z","snapshot_observed_at":"2026-08-09T07:06:38.145666Z","submitted_at":"2024-10-30T12:38:49Z","title":"Private Synthetic Text Generation with Diffusion Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.22971","snapshot_observed_at":"2026-08-04T17:03:13.046521Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.11176","last_updated":"2025-09-14T09:16:11Z","snapshot_observed_at":"2026-08-07T09:02:12.441325Z","submitted_at":"2025-09-14T09:16:11Z","title":"Differentially-private text generation degrades output language quality","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-04T17:03:13.046521Z"},"links":{"cited_paper":"/paper/2410.22971","citing_paper":"/paper/2509.11176"},"observation_digest":"sha256:9f0c882af5d12106d475123149ee1891a5901e53db8dcb97b1c2c36eea9b454c","observation_id":"774d6530-d792-4f04-b7a8-5f8317348ba1","resolution":{"observed_at":"2026-08-04T17:03:13.046521Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.22971","last_updated":"2024-10-30T12:38:49Z","snapshot_observed_at":"2026-08-09T07:06:38.145666Z","submitted_at":"2024-10-30T12:38:49Z","title":"Private Synthetic Text Generation with Diffusion Models","version":1},"cited_work":{"arxiv_id":"2410.22971","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.22971","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"ed1604cc-29eb-40eb-812f-af0ebaeec3a8","year":2024},"citing_paper":{"arxiv_id":"2603.13419","last_updated":"2026-05-20T10:08:19Z","snapshot_observed_at":"2026-07-06T22:48:57.474272Z","submitted_at":"2026-03-12T21:02:17Z","title":"Diffusion Models Memorize in Training -- and Generalize in Inference","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-21T10:52:31.849094Z"},"links":{"cited_paper":"/paper/2410.22971","citing_paper":"/paper/2603.13419"},"observation_digest":"sha256:abd35809d28380778f30e3765bc221cc4d47e1f2df60ba71a86bae57efc9e6cf","observation_id":"9f6d3412-8ad2-4ed0-bb20-516067431f0c","resolution":{"observed_at":"2026-05-21T10:54:07.892093Z","resolver_source":"arxiv_id","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/2410.22971/citation-record","integrity":"/paper/2410.22971/integrity","json":"/paper/2410.22971/citation-record.json","paper":"/paper/2410.22971"},"outbound":[],"paper":{"arxiv_id":"2410.22971","last_updated":"2024-10-30T12:38:49Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-09T07:06:38.145666Z","submitted_at":"2024-10-30T12:38:49Z","title":"Private Synthetic Text Generation with Diffusion 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 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2410.22971."}