{"as_of":"2026-08-04T07:59:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:7b6c36169c8fedc2660bef0cabb83b038032004de16ff0091172f73ee8b71125","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":"2026-08-04T06:34:03.388597+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":"2026-05-15T08:39:02.403925Z","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":"2026-05-15T08:39:52.255603Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1909.11501","last_updated":"2019-12-04T17:37:25Z","snapshot_observed_at":"2026-08-04T00:06:32.211528Z","submitted_at":"2019-09-25T14:05:02Z","title":"Disentangling to Cluster: Gaussian Mixture Variational Ladder Autoencoders","version":2},"cited_work":{"arxiv_id":"1909.11501","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1909.11501","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"206f28f1-2f2f-4970-a8bd-dd9809095039","year":2019},"citing_paper":{"arxiv_id":"2603.23547","last_updated":"2026-04-23T13:15:31Z","snapshot_observed_at":"2026-07-06T22:50:23.931381Z","submitted_at":"2026-03-20T08:54:35Z","title":"PDGMM-VAE: A Variational Autoencoder with Adaptive Per-Dimension Gaussian Mixture Model Priors for Nonlinear ICA","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-15T08:39:02.403925Z"},"links":{"cited_paper":"/paper/1909.11501","citing_paper":"/paper/2603.23547"},"observation_digest":"sha256:3daa8c2a3f460d6bc3e99a0c3c9cf2db316d5b4a21f3f177e4b4fcb71b0838d4","observation_id":"d03d6146-c147-4b3c-abb6-df487aa91347","resolution":{"observed_at":"2026-05-15T08:39:52.257022Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/1909.11501/citation-record","integrity":"/paper/1909.11501/integrity","json":"/paper/1909.11501/citation-record.json","paper":"/paper/1909.11501"},"outbound":[],"paper":{"arxiv_id":"1909.11501","last_updated":"2019-12-04T17:37:25Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-04T00:06:32.211528Z","submitted_at":"2019-09-25T14:05:02Z","title":"Disentangling to Cluster: Gaussian Mixture Variational Ladder Autoencoders"},"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":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"thesis":"As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:1909.11501."}