{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:LPROVXSTPLKIG7LORVRT4U3RBO","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":"abb4a3a3496321f5a9ae673b1fd28752addc7edc3e73280455b629693a802b6a","cross_cats_sorted":["cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-24T12:45:17Z","title_canon_sha256":"67908b525d4f3f33f7c9e2b064e0450a37d89bbc6b4dacc21d19f3e924933e8b"},"schema_version":"1.0","source":{"id":"2205.12038","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.12038","created_at":"2026-07-05T04:26:10Z"},{"alias_kind":"arxiv_version","alias_value":"2205.12038v1","created_at":"2026-07-05T04:26:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.12038","created_at":"2026-07-05T04:26:10Z"},{"alias_kind":"pith_short_12","alias_value":"LPROVXSTPLKI","created_at":"2026-07-05T04:26:10Z"},{"alias_kind":"pith_short_16","alias_value":"LPROVXSTPLKIG7LO","created_at":"2026-07-05T04:26:10Z"},{"alias_kind":"pith_short_8","alias_value":"LPROVXST","created_at":"2026-07-05T04:26:10Z"}],"graph_snapshots":[{"event_id":"sha256:fea19cd4765c6ce6d0467c83edc42db58d13572672a87ec167cb9db3876a1598","target":"graph","created_at":"2026-07-05T04:26:10Z","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/2205.12038/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Along with the popularity of Artificial Intelligence (AI) and Internet-of-Things (IoT), Federated Learning (FL) has attracted steadily increasing attentions as a promising distributed machine learning paradigm, which enables the training of a central model on for numerous decentralized devices without exposing their privacy. However, due to the biased data distributions on involved devices, FL inherently suffers from low classification accuracy in non-IID scenarios. Although various device grouping method have been proposed to address this problem, most of them neglect both i) distinct data di","authors_text":"Jun Xia, Ming Hu, Mingsong Chen, Ting Wang, Zhihao Yue, Zhiwei Ling","cross_cats":["cs.DC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-24T12:45:17Z","title":"FedEntropy: Efficient Device Grouping for Federated Learning Using Maximum Entropy Judgment"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.12038","kind":"arxiv","version":1},"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:cbb55ac692e5da46e658074fe46ccfdd00c9013001e4c16d7c00333730cd01ae","target":"record","created_at":"2026-07-05T04:26:10Z","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":"abb4a3a3496321f5a9ae673b1fd28752addc7edc3e73280455b629693a802b6a","cross_cats_sorted":["cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-24T12:45:17Z","title_canon_sha256":"67908b525d4f3f33f7c9e2b064e0450a37d89bbc6b4dacc21d19f3e924933e8b"},"schema_version":"1.0","source":{"id":"2205.12038","kind":"arxiv","version":1}},"canonical_sha256":"5be2eade537ad4837d6e8d633e53710b845333591f9c8c377c4bb57f9f123efb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5be2eade537ad4837d6e8d633e53710b845333591f9c8c377c4bb57f9f123efb","first_computed_at":"2026-07-05T04:26:10.773153Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:26:10.773153Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZlR0RTtE8OH3I1qiCyfFw3RFVnoJ/y7knrz7DnEt5TyksG/Yjny1rr8bO1irx3OdEZgng78/wfnnTEJTOtrLAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T04:26:10.773498Z","signed_message":"canonical_sha256_bytes"},"source_id":"2205.12038","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cbb55ac692e5da46e658074fe46ccfdd00c9013001e4c16d7c00333730cd01ae","sha256:fea19cd4765c6ce6d0467c83edc42db58d13572672a87ec167cb9db3876a1598"],"state_sha256":"8aecb68b94c00b87e73720d225a8bb5efb0ce1909ed489a0b2ee03d4c253c675"}