{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:YJVAY6DVS5A772PBDT7FDUEPQ3","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":"43b8d000a6147fb29947d19cff9ef39f706c8090ab0ae6494cf5c47d1bc3e925","cross_cats_sorted":["cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-09-26T07:56:10Z","title_canon_sha256":"ec1096f17748d6309ecba7e43edb651d1f5a126b6a62b1501f2a94bace525ffc"},"schema_version":"1.0","source":{"id":"2109.12519","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2109.12519","created_at":"2026-07-05T03:17:22Z"},{"alias_kind":"arxiv_version","alias_value":"2109.12519v1","created_at":"2026-07-05T03:17:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2109.12519","created_at":"2026-07-05T03:17:22Z"},{"alias_kind":"pith_short_12","alias_value":"YJVAY6DVS5A7","created_at":"2026-07-05T03:17:22Z"},{"alias_kind":"pith_short_16","alias_value":"YJVAY6DVS5A772PB","created_at":"2026-07-05T03:17:22Z"},{"alias_kind":"pith_short_8","alias_value":"YJVAY6DV","created_at":"2026-07-05T03:17:22Z"}],"graph_snapshots":[{"event_id":"sha256:f9ddd92d725d99c8d716fe8c55b750fbabb20281afc20620f807d85997b1c44f","target":"graph","created_at":"2026-07-05T03:17:22Z","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/2109.12519/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Vertical federated learning (VFL) is an effective paradigm of training the emerging cross-organizational (e.g., different corporations, companies and organizations) collaborative learning with privacy preserving. Stochastic gradient descent (SGD) methods are the popular choices for training VFL models because of the low per-iteration computation. However, existing SGD-based VFL algorithms are communication-expensive due to a large number of communication rounds. Meanwhile, most existing VFL algorithms use synchronous computation which seriously hamper the computation resource utilization in re","authors_text":"Bin Gu, Cheng Deng, Heng Huang, Jian Pei, Liefeng Bo, Qingsong Zhang, Songxiang Gu","cross_cats":["cs.DC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-09-26T07:56:10Z","title":"AsySQN: Faster Vertical Federated Learning Algorithms with Better Computation Resource Utilization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2109.12519","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:f8b185b1f1857e8ddbbfac76d3c22dab6c47b3d3fa40ee03faad6dc2d1ea7060","target":"record","created_at":"2026-07-05T03:17:22Z","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":"43b8d000a6147fb29947d19cff9ef39f706c8090ab0ae6494cf5c47d1bc3e925","cross_cats_sorted":["cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-09-26T07:56:10Z","title_canon_sha256":"ec1096f17748d6309ecba7e43edb651d1f5a126b6a62b1501f2a94bace525ffc"},"schema_version":"1.0","source":{"id":"2109.12519","kind":"arxiv","version":1}},"canonical_sha256":"c26a0c78759741ffe9e11cfe51d08f86dd8d2d110ff390bf26c06adb45ac0666","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c26a0c78759741ffe9e11cfe51d08f86dd8d2d110ff390bf26c06adb45ac0666","first_computed_at":"2026-07-05T03:17:22.049747Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:17:22.049747Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"oMfUTWZCYkO4/9cHWmAC/aHSMc4eMT0jc/rfEGiFlA7C6YJ6KFI3EoZBo0RyXrfKe2MhECRxAvBhhu/lzZjsDw==","signature_status":"signed_v1","signed_at":"2026-07-05T03:17:22.050129Z","signed_message":"canonical_sha256_bytes"},"source_id":"2109.12519","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f8b185b1f1857e8ddbbfac76d3c22dab6c47b3d3fa40ee03faad6dc2d1ea7060","sha256:f9ddd92d725d99c8d716fe8c55b750fbabb20281afc20620f807d85997b1c44f"],"state_sha256":"31512a6ed3acaf73433cb56676160fbd4b654abe4cd4bd474be094e9bb378606"}