{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:CF4ZDVDBDNTLEFD6QFKUMUZ55J","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"dd1dc1d22a445704a32cf3dd2c888c8d92185f1415ea2d1887a6470a405029fa","cross_cats_sorted":["cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-02-26T13:07:43Z","title_canon_sha256":"59164895ee0df5bf1499d942b3a43d62d4d4479f81afe3704d615bf16dab267c"},"schema_version":"1.0","source":{"id":"2102.13451","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2102.13451","created_at":"2026-07-05T03:47:14Z"},{"alias_kind":"arxiv_version","alias_value":"2102.13451v5","created_at":"2026-07-05T03:47:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2102.13451","created_at":"2026-07-05T03:47:14Z"},{"alias_kind":"pith_short_12","alias_value":"CF4ZDVDBDNTL","created_at":"2026-07-05T03:47:14Z"},{"alias_kind":"pith_short_16","alias_value":"CF4ZDVDBDNTLEFD6","created_at":"2026-07-05T03:47:14Z"},{"alias_kind":"pith_short_8","alias_value":"CF4ZDVDB","created_at":"2026-07-05T03:47:14Z"}],"graph_snapshots":[{"event_id":"sha256:55e36767ee0e9e1db3ccbbbf78b6ebf48455b841129cc8e9ba3ea270d2e4485c","target":"graph","created_at":"2026-07-05T03:47:14Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2102.13451/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Federated Learning (FL) has been gaining significant traction across different ML tasks, ranging from vision to keyboard predictions. In large-scale deployments, client heterogeneity is a fact and constitutes a primary problem for fairness, training performance and accuracy. Although significant efforts have been made into tackling statistical data heterogeneity, the diversity in the processing capabilities and network bandwidth of clients, termed as system heterogeneity, has remained largely unexplored. Current solutions either disregard a large portion of available devices or set a uniform l","authors_text":"Ilias Leontiadis, Mario Almeida, Nicholas D. Lane, Samuel Horvath, Stefanos Laskaridis, Stylianos I. Venieris","cross_cats":["cs.DC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-02-26T13:07:43Z","title":"FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2102.13451","kind":"arxiv","version":5},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:cfbcb6d781c36a0b8b8a762c5d0e4c8a488bde5fb1216461ff95e5ed5f37ec36","target":"record","created_at":"2026-07-05T03:47:14Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"dd1dc1d22a445704a32cf3dd2c888c8d92185f1415ea2d1887a6470a405029fa","cross_cats_sorted":["cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-02-26T13:07:43Z","title_canon_sha256":"59164895ee0df5bf1499d942b3a43d62d4d4479f81afe3704d615bf16dab267c"},"schema_version":"1.0","source":{"id":"2102.13451","kind":"arxiv","version":5}},"canonical_sha256":"117991d4611b66b2147e815546533dea5e5beb283d2932f2c6be2b68055bbab7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"117991d4611b66b2147e815546533dea5e5beb283d2932f2c6be2b68055bbab7","first_computed_at":"2026-07-05T03:47:14.725714Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:47:14.725714Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"NVH2pRXOHt5Aaf5UN2pdTAxK60Eo+C9h0SLD8PEEtVzrSfX28CsjoQH7HzI8JUJMQMNaRXGDN7OuzfBzpRN+CA==","signature_status":"signed_v1","signed_at":"2026-07-05T03:47:14.726771Z","signed_message":"canonical_sha256_bytes"},"source_id":"2102.13451","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cfbcb6d781c36a0b8b8a762c5d0e4c8a488bde5fb1216461ff95e5ed5f37ec36","sha256:55e36767ee0e9e1db3ccbbbf78b6ebf48455b841129cc8e9ba3ea270d2e4485c"],"state_sha256":"af4618db03d87c9efb79869413c22085c1f5023a0035edde633b9e7ffa5ceecc"}