{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:GM3RGD5MFICJWPAQ4V277S26FF","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":"e85305c27ee458001a6364c62db1ae5f66d76f9b4ee79401faa6ed760c1873df","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-03-05T02:31:32Z","title_canon_sha256":"3ea8d3004e5abec364e6473c6d6758f2c5062eaae8fdcff2cded063be6ce4cec"},"schema_version":"1.0","source":{"id":"2203.02645","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.02645","created_at":"2026-07-05T04:02:25Z"},{"alias_kind":"arxiv_version","alias_value":"2203.02645v1","created_at":"2026-07-05T04:02:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.02645","created_at":"2026-07-05T04:02:25Z"},{"alias_kind":"pith_short_12","alias_value":"GM3RGD5MFICJ","created_at":"2026-07-05T04:02:25Z"},{"alias_kind":"pith_short_16","alias_value":"GM3RGD5MFICJWPAQ","created_at":"2026-07-05T04:02:25Z"},{"alias_kind":"pith_short_8","alias_value":"GM3RGD5M","created_at":"2026-07-05T04:02:25Z"}],"graph_snapshots":[{"event_id":"sha256:cfc35d6f09747bb0a591d2c85ae69e314b94e65372387cdd50a021382b20194c","target":"graph","created_at":"2026-07-05T04:02:25Z","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/2203.02645/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Federated learning (FL) enables distributed optimization of machine learning models while protecting privacy by independently training local models on each client and then aggregating parameters on a central server, thereby producing an effective global model. Although a variety of FL algorithms have been proposed, their training efficiency remains low when the data are not independently and identically distributed (non-i.i.d.) across different clients. We observe that the slow convergence rates of the existing methods are (at least partially) caused by the catastrophic forgetting issue during","authors_text":"Chencheng Xu, Minlie Huang, Tao Jiang, Zhiwei Hong","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-03-05T02:31:32Z","title":"Acceleration of Federated Learning with Alleviated Forgetting in Local Training"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.02645","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":"sha256:4b9419102f40535c2ec89e83ee2f3f65b567e19bc3125a5a97217c1585cd48df","target":"record","created_at":"2026-07-05T04:02:25Z","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":"e85305c27ee458001a6364c62db1ae5f66d76f9b4ee79401faa6ed760c1873df","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-03-05T02:31:32Z","title_canon_sha256":"3ea8d3004e5abec364e6473c6d6758f2c5062eaae8fdcff2cded063be6ce4cec"},"schema_version":"1.0","source":{"id":"2203.02645","kind":"arxiv","version":1}},"canonical_sha256":"3337130fac2a049b3c10e575ffcb5e297d79bcaf0c1522c98e3c7a71ef355a0a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3337130fac2a049b3c10e575ffcb5e297d79bcaf0c1522c98e3c7a71ef355a0a","first_computed_at":"2026-07-05T04:02:25.485831Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:02:25.485831Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0+YndtuItqzGX9+JzgIuKIv+WHQNJkGdVlJ5LqoCL+ZzHq3gEDacyuqMRBt5JqmMR/TimfpJJAYvujtJlsLXCA==","signature_status":"signed_v1","signed_at":"2026-07-05T04:02:25.486357Z","signed_message":"canonical_sha256_bytes"},"source_id":"2203.02645","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4b9419102f40535c2ec89e83ee2f3f65b567e19bc3125a5a97217c1585cd48df","sha256:cfc35d6f09747bb0a591d2c85ae69e314b94e65372387cdd50a021382b20194c"],"state_sha256":"cc310e2fff632d538d9a1df9de490eab3d069d9469c594e1caef935ae974ee61"}