{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:LK7X4YQT2EIFHXZ7Y5DCT7WO7O","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":"b4dbb5c2952e7f91c8a962ee796fdcaae1fd55440e3b8df21faa44cdaa2e673b","cross_cats_sorted":["cs.AI","cs.CR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-10-22T08:22:36Z","title_canon_sha256":"9500b58e31737b4539789cb3fdaa83db83106d3ac5d7bc3b4032345b3396a54a"},"schema_version":"1.0","source":{"id":"2110.12906","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.12906","created_at":"2026-07-05T08:58:38Z"},{"alias_kind":"arxiv_version","alias_value":"2110.12906v3","created_at":"2026-07-05T08:58:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.12906","created_at":"2026-07-05T08:58:38Z"},{"alias_kind":"pith_short_12","alias_value":"LK7X4YQT2EIF","created_at":"2026-07-05T08:58:38Z"},{"alias_kind":"pith_short_16","alias_value":"LK7X4YQT2EIFHXZ7","created_at":"2026-07-05T08:58:38Z"},{"alias_kind":"pith_short_8","alias_value":"LK7X4YQT","created_at":"2026-07-05T08:58:38Z"}],"graph_snapshots":[{"event_id":"sha256:ac1e3517129de5059eeb9e20e0ce9ef3cead273978bb629c776e0534f1892d90","target":"graph","created_at":"2026-07-05T08:58:38Z","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/2110.12906/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Federated graph learning (FGL) has become an important research topic in response to the increasing scale and the distributed nature of graph-structured data in the real world. In FGL, a global graph is distributed across different clients, where each client holds a subgraph. Existing FGL methods often fail to effectively utilize cross-client edges, losing structural information during the training; additionally, local graphs often exhibit significant distribution divergence. These two issues make local models in FGL less desirable than in centralized graph learning, namely the local bias prob","authors_text":"Binchi Zhang, Jun Zhou, Minnan Luo, Qinghua Zheng, Shangbin Feng, Ziqi Liu","cross_cats":["cs.AI","cs.CR"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-10-22T08:22:36Z","title":"Tackling the Local Bias in Federated Graph Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.12906","kind":"arxiv","version":3},"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":"sha256:309e76135d7a0f0e37a86cd72d6feca60f025ec4e5b5e10e020d743926dc8d32","target":"record","created_at":"2026-07-05T08:58:38Z","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":"b4dbb5c2952e7f91c8a962ee796fdcaae1fd55440e3b8df21faa44cdaa2e673b","cross_cats_sorted":["cs.AI","cs.CR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-10-22T08:22:36Z","title_canon_sha256":"9500b58e31737b4539789cb3fdaa83db83106d3ac5d7bc3b4032345b3396a54a"},"schema_version":"1.0","source":{"id":"2110.12906","kind":"arxiv","version":3}},"canonical_sha256":"5abf7e6213d11053df3fc74629fecefb9729fa9210211445e90ecb1e8f44e85f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5abf7e6213d11053df3fc74629fecefb9729fa9210211445e90ecb1e8f44e85f","first_computed_at":"2026-07-05T08:58:38.784485Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:58:38.784485Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9I9njeZG/u8rlEHUMTtDpaHKnEX3oEbmHUhQNue5rh32eQ9/EeZPw7l1EWqadcbdQKl8QDSCnkoRb2TpTcfgCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:58:38.787878Z","signed_message":"canonical_sha256_bytes"},"source_id":"2110.12906","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:309e76135d7a0f0e37a86cd72d6feca60f025ec4e5b5e10e020d743926dc8d32","sha256:ac1e3517129de5059eeb9e20e0ce9ef3cead273978bb629c776e0534f1892d90"],"state_sha256":"276418cb1bb95a18afcb151d64223104d58e5cacd77044c538a77919478102b5"}