{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:AHGCR3YUBJJFCPDQVJCVBUVR4X","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":"7a278a86bef55f36b03bad5f34f27d96b1dade1d462f44833b8923e7ebc4bf42","cross_cats_sorted":["cs.DC","cs.NI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-05-24T05:39:24Z","title_canon_sha256":"ecc054428d655cb62d4af0ba84a12cb626f3eb24e3ffd2fed381d947677d429c"},"schema_version":"1.0","source":{"id":"2105.11099","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2105.11099","created_at":"2026-07-05T02:42:35Z"},{"alias_kind":"arxiv_version","alias_value":"2105.11099v1","created_at":"2026-07-05T02:42:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2105.11099","created_at":"2026-07-05T02:42:35Z"},{"alias_kind":"pith_short_12","alias_value":"AHGCR3YUBJJF","created_at":"2026-07-05T02:42:35Z"},{"alias_kind":"pith_short_16","alias_value":"AHGCR3YUBJJFCPDQ","created_at":"2026-07-05T02:42:35Z"},{"alias_kind":"pith_short_8","alias_value":"AHGCR3YU","created_at":"2026-07-05T02:42:35Z"}],"graph_snapshots":[{"event_id":"sha256:d8c85bf1e3cf61ec153811b3343278a0bc7067d931f201742d1ecf32cb5e4d14","target":"graph","created_at":"2026-07-05T02:42:35Z","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/2105.11099/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Graph neural networks (GNN) have been successful in many fields, and derived various researches and applications in real industries. However, in some privacy sensitive scenarios (like finance, healthcare), training a GNN model centrally faces challenges due to the distributed data silos. Federated learning (FL) is a an emerging technique that can collaboratively train a shared model while keeping the data decentralized, which is a rational solution for distributed GNN training. We term it as federated graph learning (FGL). Although FGL has received increasing attention recently, the definition","authors_text":"Chao Wu, Fei Wu, Hongxia Yang, Huanding Zhang, Mingyang Yin, Tao Shen","cross_cats":["cs.DC","cs.NI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-05-24T05:39:24Z","title":"Federated Graph Learning -- A Position Paper"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2105.11099","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:ccf316ece27f98fb7df20f5ad0c1b07cdacc3ea7e3b9483e5b2642213f8cfd63","target":"record","created_at":"2026-07-05T02:42:35Z","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":"7a278a86bef55f36b03bad5f34f27d96b1dade1d462f44833b8923e7ebc4bf42","cross_cats_sorted":["cs.DC","cs.NI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-05-24T05:39:24Z","title_canon_sha256":"ecc054428d655cb62d4af0ba84a12cb626f3eb24e3ffd2fed381d947677d429c"},"schema_version":"1.0","source":{"id":"2105.11099","kind":"arxiv","version":1}},"canonical_sha256":"01cc28ef140a52513c70aa4550d2b1e5f6a7929c191216dbc94b58fdc790d9df","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"01cc28ef140a52513c70aa4550d2b1e5f6a7929c191216dbc94b58fdc790d9df","first_computed_at":"2026-07-05T02:42:35.447422Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:42:35.447422Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FnX6GWKeoyfAJTEnvHt3oMSBV6JZXMIHvj6UnNyMMcVKvdxg1QP5Z2hDvZzl7EcjDLNy29DiCrB/cLHvWK6dDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T02:42:35.447909Z","signed_message":"canonical_sha256_bytes"},"source_id":"2105.11099","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ccf316ece27f98fb7df20f5ad0c1b07cdacc3ea7e3b9483e5b2642213f8cfd63","sha256:d8c85bf1e3cf61ec153811b3343278a0bc7067d931f201742d1ecf32cb5e4d14"],"state_sha256":"a1a0c41c5f96a605bae4a72c608c3927b2ef746aa603f8e6ef2c80307a12b3b0"}