{"as_of":"2026-08-08T22:37:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:cea6fe491c411c4534ccadfeb9dd276425bd6298089f376f5734d08be11b8fda","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":"2026-08-08T06:32:00.761636+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":"2026-08-05T10:44:00.844806Z","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":"2026-08-05T10:44:00.985131Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2206.07977","last_updated":"2022-06-16T07:37:02Z","snapshot_observed_at":"2026-08-02T10:20:42.304329Z","submitted_at":"2022-06-16T07:37:02Z","title":"Personalized Federated Learning via Variational Bayesian Inference","version":1},"cited_work":{"arxiv_id":"2206.07977","doi":null,"metadata_source":"pith","pith_arxiv_id":"2206.07977","snapshot_observed_at":"2026-08-05T10:44:00.985131Z","title":"Personalized Federated Learning via Variational Bayesian Inference","venue":"cs.LG","work_id":"10d632f0-4455-4275-a0ce-6b1555b91d30","year":2022},"citing_paper":{"arxiv_id":"2509.10521","last_updated":"2025-09-04T01:28:02Z","snapshot_observed_at":"2026-08-08T12:50:59.610183Z","submitted_at":"2025-09-04T01:28:02Z","title":"Variational Gaussian Mixture Manifold Models for Client-Specific Federated Personalization","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-05T10:44:00.844806Z"},"links":{"cited_paper":"/paper/2206.07977","citing_paper":"/paper/2509.10521"},"observation_digest":"sha256:4e14a9703d8757cb22b956d465ec3440f02a1a1a9f2c2a1660626067c6ddc29a","observation_id":"0d072c16-5b30-4eb7-9fc8-66bf332b893d","resolution":{"observed_at":"2026-08-05T10:44:01.045980Z","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/2206.07977/citation-record","integrity":"/paper/2206.07977/integrity","json":"/paper/2206.07977/citation-record.json","paper":"/paper/2206.07977"},"outbound":[],"paper":{"arxiv_id":"2206.07977","last_updated":"2022-06-16T07:37:02Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-02T10:20:42.304329Z","submitted_at":"2022-06-16T07:37:02Z","title":"Personalized Federated Learning via Variational Bayesian Inference"},"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 1 inbound Pith citation observation for arXiv:2206.07977."}