{"as_of":"2026-08-16T11:27:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ba16defc25df8994502e7fdcba5dec6888cd27e55322198ca9dcf954e07a362e","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":2,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":2,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T21:39:35.604302Z","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":"2026-07-03T06:17:42.592018Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2404.09292","last_updated":"2024-12-24T14:07:46Z","snapshot_observed_at":"2026-08-13T00:30:30.291532Z","submitted_at":"2024-04-14T15:58:35Z","title":"Bridging Data Islands: Geographic Heterogeneity-Aware Federated Learning for Collaborative Remote Sensing Semantic Segmentation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.09292","snapshot_observed_at":"2026-08-15T21:39:35.604302Z","title":"Bridging data islands: Geographic heterogeneity-aware federated learning for collaborative remote sensing seman- tic segmentation.arXiv preprint arXiv:2404.09292,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.09385","last_updated":"2025-05-14T13:38:30Z","snapshot_observed_at":"2026-08-15T21:30:48.321874Z","submitted_at":"2025-05-14T13:38:30Z","title":"FedSaaS: Class-Consistency Federated Semantic Segmentation via Global Prototype Supervision and Local Adversarial Harmonization","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-15T21:39:35.604302Z"},"links":{"cited_paper":"/paper/2404.09292","citing_paper":"/paper/2505.09385"},"observation_digest":"sha256:0da33caab23a040192dae63f19b63741acdd04d28c188a32af42392b05262519","observation_id":"4b2cb670-e56c-41de-a334-a4809434c565","resolution":{"observed_at":"2026-08-15T21:39:35.604302Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.09292","last_updated":"2024-12-24T14:07:46Z","snapshot_observed_at":"2026-08-13T00:30:30.291532Z","submitted_at":"2024-04-14T15:58:35Z","title":"Bridging Data Islands: Geographic Heterogeneity-Aware Federated Learning for Collaborative Remote Sensing Semantic Segmentation","version":2},"cited_work":{"arxiv_id":"2404.09292","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2404.09292","snapshot_observed_at":"2026-07-03T06:17:42.592018Z","title":null,"venue":null,"work_id":"9043e84d-41f0-47dc-af91-51804e4ec1fd","year":2024},"citing_paper":{"arxiv_id":"2606.10595","last_updated":"2026-06-09T09:00:04Z","snapshot_observed_at":"2026-08-13T03:36:12.735158Z","submitted_at":"2026-06-09T09:00:04Z","title":"From Data Heterogeneity to Convergence: A Data-Centric Review of Federated Learning","version":1},"reference_index":92,"source":"pdf_text","source_observed_at":"2026-06-27T12:42:08.487008Z"},"links":{"cited_paper":"/paper/2404.09292","citing_paper":"/paper/2606.10595"},"observation_digest":"sha256:30adf7673d13e87537f5f53f380c33e153b2fd83ac9345ea2706ef9a7cfd4528","observation_id":"a58893c3-9571-4ea7-8f64-86623f6e25aa","resolution":{"observed_at":"2026-07-03T06:17:42.593308Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2404.09292/citation-record","integrity":"/paper/2404.09292/integrity","json":"/paper/2404.09292/citation-record.json","paper":"/paper/2404.09292"},"outbound":[],"paper":{"arxiv_id":"2404.09292","last_updated":"2024-12-24T14:07:46Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-13T00:30:30.291532Z","submitted_at":"2024-04-14T15:58:35Z","title":"Bridging Data Islands: Geographic Heterogeneity-Aware Federated Learning for Collaborative Remote Sensing Semantic Segmentation"},"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":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2404.09292."}