{"as_of":"2026-08-07T20:55:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4ad57618e89f6dc8405c30e4b64df9d92b5f5eefdfb8f59a794150c42f6a1be7","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":"2026-08-07T06:34:17.273281+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":"2026-08-07T05:22:27.669371Z","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":"2026-08-07T05:22:27.849051Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2107.00233","last_updated":"2021-07-01T06:14:51Z","snapshot_observed_at":"2026-08-03T09:34:51.063276Z","submitted_at":"2021-07-01T06:14:51Z","title":"FedMix: Approximation of Mixup under Mean Augmented Federated Learning","version":1},"cited_work":{"arxiv_id":"2107.00233","doi":null,"metadata_source":"pith","pith_arxiv_id":"2107.00233","snapshot_observed_at":"2026-08-07T05:22:27.849051Z","title":"FedMix: Approximation of Mixup under Mean Augmented Federated Learning","venue":"cs.LG","work_id":"da2e6c8c-627e-4786-b3e7-465914f76b68","year":2021},"citing_paper":{"arxiv_id":"2506.08167","last_updated":"2025-06-09T19:25:35Z","snapshot_observed_at":"2026-08-07T10:06:04.881895Z","submitted_at":"2025-06-09T19:25:35Z","title":"UniVarFL: Uniformity and Variance Regularized Federated Learning for Heterogeneous Data","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T05:22:27.669371Z"},"links":{"cited_paper":"/paper/2107.00233","citing_paper":"/paper/2506.08167"},"observation_digest":"sha256:5869d23070bd99326596ed9df2dc88a436b7a5fa02f6da32e867d898d3371e5f","observation_id":"55674224-e855-46a7-8d06-65dea2983499","resolution":{"observed_at":"2026-08-07T05:22:27.855725Z","resolver_source":"local_arxiv","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"}}],"links":{"evidence":"/evidence","html":"/paper/2107.00233/citation-record","integrity":"/paper/2107.00233/integrity","json":"/paper/2107.00233/citation-record.json","paper":"/paper/2107.00233"},"outbound":[],"paper":{"arxiv_id":"2107.00233","last_updated":"2021-07-01T06:14:51Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-03T09:34:51.063276Z","submitted_at":"2021-07-01T06:14:51Z","title":"FedMix: Approximation of Mixup under Mean Augmented Federated Learning"},"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 1 inbound Pith citation observation for arXiv:2107.00233."}