{"as_of":"2026-08-18T09:33:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2a1e5b3193e62e07163b6f11bcbec7d1b9d2a44f3f846db68406986e7ab268ce","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":"2026-08-18T06:34:40.430872+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":"2026-08-15T23:30:59.082204Z","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":"2026-08-15T23:30:59.344787Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2402.10456","last_updated":"2025-01-07T10:03:08Z","snapshot_observed_at":"2026-08-16T14:18:06.364363Z","submitted_at":"2024-02-16T05:27:05Z","title":"Efficient Generative Modeling via Penalized Optimal Transport Network","version":2},"cited_work":{"arxiv_id":"2402.10456","doi":null,"metadata_source":"pith","pith_arxiv_id":"2402.10456","snapshot_observed_at":"2026-08-15T23:30:59.344787Z","title":"Efficient Generative Modeling via Penalized Optimal Transport Network","venue":"stat.ML","work_id":"55b455f2-055e-4602-b4fb-ed208f138a68","year":2024},"citing_paper":{"arxiv_id":"2505.04603","last_updated":"2025-05-07T17:50:14Z","snapshot_observed_at":"2026-08-15T23:22:17.569334Z","submitted_at":"2025-05-07T17:50:14Z","title":"Likelihood-Free Adaptive Bayesian Inference via Nonparametric Distribution Matching","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:59.082204Z"},"links":{"cited_paper":"/paper/2402.10456","citing_paper":"/paper/2505.04603"},"observation_digest":"sha256:1bd2f7f73ce850c473b5af2b19c02043831fe1092ad7455662455a3821181d9d","observation_id":"7ea9ba39-ce66-49b3-91f2-78a251c670a1","resolution":{"observed_at":"2026-08-15T23:30:59.351157Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2402.10456/citation-record","integrity":"/paper/2402.10456/integrity","json":"/paper/2402.10456/citation-record.json","paper":"/paper/2402.10456"},"outbound":[],"paper":{"arxiv_id":"2402.10456","last_updated":"2025-01-07T10:03:08Z","latest_version":2,"primary_category":"stat.ML","snapshot_observed_at":"2026-08-16T14:18:06.364363Z","submitted_at":"2024-02-16T05:27:05Z","title":"Efficient Generative Modeling via Penalized Optimal Transport Network"},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2402.10456."}