{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:QPOHTP2D56OW5UN57SHAHJNR3P","short_pith_number":"pith:QPOHTP2D","schema_version":"1.0","canonical_sha256":"83dc79bf43ef9d6ed1bdfc8e03a5b1dbcb2432ba023a7239a599e41e49487b48","source":{"kind":"arxiv","id":"2608.09687","version":1},"attestation_state":"computed","paper":{"title":"FedOrbit: Adaptive Personalized Federated Learning for Non-IID LEO Satellite Constellations","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Muddesar Iqbal, Satwat Bashir, Tasos Dagiuklas","submitted_at":"2026-08-10T14:53:48Z","abstract_excerpt":"Federated learning (FL) in Low Earth Orbit (LEO) satellite constellations is affected by non-IID data and irregular ground-station visibility, both driven by orbital geometry. Global aggregation performs poorly when orbit-level class distributions are disjoint, while strong personalisation can be excessive when these distributions overlap. We present FedOrbit, which combines continuous orbit-level training over inter-satellite links, class-aware hierarchical aggregation, quality-weighted feature aggregation with return-rate dampening, and adaptive feature decomposition based on inter-orbit cla"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2608.09687","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-08-10T14:53:48Z","cross_cats_sorted":[],"title_canon_sha256":"7735ad9a7d1e19cbdd403ff21e93d02b93cdee1c6690defa93d463682e897733","abstract_canon_sha256":"129b2a03c38a040b1186b9ed7b37993d721d5c8c8fa86cf74c608bc93d232666"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-11T02:24:48.956322Z","signature_b64":"qqU5lRDuNSUeqDojIBRGILmZ+Pvh2j2NjIRhvAoJoh4ZM9M4uRBM/KvjVabSyniELE92fsvBgz1z288fXv8RAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"83dc79bf43ef9d6ed1bdfc8e03a5b1dbcb2432ba023a7239a599e41e49487b48","last_reissued_at":"2026-08-11T02:24:48.954835Z","signature_status":"signed_v1","first_computed_at":"2026-08-11T02:24:48.954835Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"FedOrbit: Adaptive Personalized Federated Learning for Non-IID LEO Satellite Constellations","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Muddesar Iqbal, Satwat Bashir, Tasos Dagiuklas","submitted_at":"2026-08-10T14:53:48Z","abstract_excerpt":"Federated learning (FL) in Low Earth Orbit (LEO) satellite constellations is affected by non-IID data and irregular ground-station visibility, both driven by orbital geometry. Global aggregation performs poorly when orbit-level class distributions are disjoint, while strong personalisation can be excessive when these distributions overlap. We present FedOrbit, which combines continuous orbit-level training over inter-satellite links, class-aware hierarchical aggregation, quality-weighted feature aggregation with return-rate dampening, and adaptive feature decomposition based on inter-orbit cla"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.09687","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2608.09687/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2608.09687","created_at":"2026-08-11T02:24:48.955415+00:00"},{"alias_kind":"arxiv_version","alias_value":"2608.09687v1","created_at":"2026-08-11T02:24:48.955415+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.09687","created_at":"2026-08-11T02:24:48.955415+00:00"},{"alias_kind":"pith_short_12","alias_value":"QPOHTP2D56OW","created_at":"2026-08-11T02:24:48.955415+00:00"},{"alias_kind":"pith_short_16","alias_value":"QPOHTP2D56OW5UN5","created_at":"2026-08-11T02:24:48.955415+00:00"},{"alias_kind":"pith_short_8","alias_value":"QPOHTP2D","created_at":"2026-08-11T02:24:48.955415+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/QPOHTP2D56OW5UN57SHAHJNR3P","json":"https://pith.science/pith/QPOHTP2D56OW5UN57SHAHJNR3P.json","graph_json":"https://pith.science/api/pith-number/QPOHTP2D56OW5UN57SHAHJNR3P/graph.json","events_json":"https://pith.science/api/pith-number/QPOHTP2D56OW5UN57SHAHJNR3P/events.json","paper":"https://pith.science/paper/QPOHTP2D"},"agent_actions":{"view_html":"https://pith.science/pith/QPOHTP2D56OW5UN57SHAHJNR3P","download_json":"https://pith.science/pith/QPOHTP2D56OW5UN57SHAHJNR3P.json","view_paper":"https://pith.science/paper/QPOHTP2D","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2608.09687&json=true","fetch_graph":"https://pith.science/api/pith-number/QPOHTP2D56OW5UN57SHAHJNR3P/graph.json","fetch_events":"https://pith.science/api/pith-number/QPOHTP2D56OW5UN57SHAHJNR3P/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QPOHTP2D56OW5UN57SHAHJNR3P/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QPOHTP2D56OW5UN57SHAHJNR3P/action/storage_attestation","attest_author":"https://pith.science/pith/QPOHTP2D56OW5UN57SHAHJNR3P/action/author_attestation","sign_citation":"https://pith.science/pith/QPOHTP2D56OW5UN57SHAHJNR3P/action/citation_signature","submit_replication":"https://pith.science/pith/QPOHTP2D56OW5UN57SHAHJNR3P/action/replication_record"}},"created_at":"2026-08-11T02:24:48.955415+00:00","updated_at":"2026-08-11T02:24:48.955415+00:00"}