{"as_of":"2026-08-07T20:04:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d2a72bd866dc8b9b446fd9aa1522a8172ef8be73ada7e0fdadd0734b6e2d2662","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":4,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":4,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T11:16:20.795118Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":82,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2102.02079","last_updated":"2021-10-28T15:22:21Z","snapshot_observed_at":"2026-08-05T23:24:43.659689Z","submitted_at":"2021-02-03T14:29:09Z","title":"Federated Learning on Non-IID Data Silos: An Experimental Study","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2102.02079","snapshot_observed_at":"2026-08-07T11:16:20.795118Z","title":"Federated learning on non-iid data silos: An experimental study, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.03337","last_updated":"2025-06-03T19:29:50Z","snapshot_observed_at":"2026-08-07T11:03:19.477293Z","submitted_at":"2025-06-03T19:29:50Z","title":"Mitigating Non-IID Drift in Zeroth-Order Federated LLM Fine-Tuning with Transferable Sparsity","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T11:16:20.795118Z"},"links":{"cited_paper":"/paper/2102.02079","citing_paper":"/paper/2506.03337"},"observation_digest":"sha256:6ae48baf16c87eec75de5a08856ee55826ff65eed0e4d313af171be4a6f8b9cb","observation_id":"8d84fb4a-c071-4788-ae19-6cf762a36e35","resolution":{"observed_at":"2026-08-07T11:16:20.795118Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2102.02079","last_updated":"2021-10-28T15:22:21Z","snapshot_observed_at":"2026-08-05T23:24:43.659689Z","submitted_at":"2021-02-03T14:29:09Z","title":"Federated Learning on Non-IID Data Silos: An Experimental Study","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2102.02079","snapshot_observed_at":"2026-08-06T19:20:31.681560Z","title":"Federated learning on non-iid data silos: An exper- imental study,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.06031","last_updated":"2025-07-08T14:34:32Z","snapshot_observed_at":"2026-08-07T09:30:03.643953Z","submitted_at":"2025-07-08T14:34:32Z","title":"Efficient Federated Learning with Timely Update Dissemination","version":1},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-08-06T19:20:31.681560Z"},"links":{"cited_paper":"/paper/2102.02079","citing_paper":"/paper/2507.06031"},"observation_digest":"sha256:bb2cfb3b29d14db67f31cc4d08425ab3eda3bae7acd86dd0c4f16d10f93f92b2","observation_id":"5ff7a6de-9535-4a02-9e9b-6f5938be6791","resolution":{"observed_at":"2026-08-06T19:20:31.681560Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2102.02079","last_updated":"2021-10-28T15:22:21Z","snapshot_observed_at":"2026-08-05T23:24:43.659689Z","submitted_at":"2021-02-03T14:29:09Z","title":"Federated Learning on Non-IID Data Silos: An Experimental Study","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2102.02079","snapshot_observed_at":"2026-08-05T13:16:20.365497Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.00799","last_updated":"2025-08-31T11:16:16Z","snapshot_observed_at":"2026-08-05T13:16:18.373423Z","submitted_at":"2025-08-31T11:16:16Z","title":"Fairness in Federated Learning: Trends, Challenges, and Opportunities","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-05T13:16:20.365497Z"},"links":{"cited_paper":"/paper/2102.02079","citing_paper":"/paper/2509.00799"},"observation_digest":"sha256:6b3fe17923725ce15ac29bfb6b0434e00a4c025feb4049aa8bd11cde99d8ddaa","observation_id":"675f2064-3b92-4c7f-8a08-8b34af5de9ae","resolution":{"observed_at":"2026-08-05T13:16:20.365497Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2102.02079","last_updated":"2021-10-28T15:22:21Z","snapshot_observed_at":"2026-08-05T23:24:43.659689Z","submitted_at":"2021-02-03T14:29:09Z","title":"Federated Learning on Non-IID Data Silos: An Experimental Study","version":4},"cited_work":{"arxiv_id":"2102.02079","doi":"10.48550/arxiv.2102.02079","metadata_source":"arxiv_reference","pith_arxiv_id":"2102.02079","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Federated Learning on Non-IID Data Silos: An Experimental Study","venue":"arXiv (Cornell University)","work_id":"3f498d27-4767-4cdf-a2f3-44c36ff98b4d","year":2021},"citing_paper":{"arxiv_id":"2604.08056","last_updated":"2026-04-09T10:08:28Z","snapshot_observed_at":"2026-07-06T22:57:13.745326Z","submitted_at":"2026-04-09T10:08:28Z","title":"Automating aggregation strategy selection in federated learning","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-10T17:32:03.728545Z"},"links":{"cited_paper":"/paper/2102.02079","citing_paper":"/paper/2604.08056"},"observation_digest":"sha256:322d0fe0426c0bc0e2f51c92f122eb1d8f673b0f84e29f9a5b35e5508b00b3f6","observation_id":"040637f5-b230-481c-915c-24448b283fdb","resolution":{"observed_at":"2026-05-10T17:35:40.313868Z","resolver_source":"arxiv_id","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/2102.02079/citation-record","integrity":"/paper/2102.02079/integrity","json":"/paper/2102.02079/citation-record.json","paper":"/paper/2102.02079"},"outbound":[],"paper":{"arxiv_id":"2102.02079","last_updated":"2021-10-28T15:22:21Z","latest_version":4,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-05T23:24:43.659689Z","submitted_at":"2021-02-03T14:29:09Z","title":"Federated Learning on Non-IID Data Silos: An Experimental Study"},"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 4 inbound Pith citation observations for arXiv:2102.02079."}