{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:IDFZN2OEL5ERFHS5OIQVHLBJSR","short_pith_number":"pith:IDFZN2OE","canonical_record":{"source":{"id":"2210.13686","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-10-25T01:08:20Z","cross_cats_sorted":[],"title_canon_sha256":"0f2f26199f2e1d5918eabbfc64e00aa6e0443688a93d801970a1aff241b84d8d","abstract_canon_sha256":"01a858b9d8caf3d7ba50301b565675e4df3a6a07b0bb256b820668650c5d8d7e"},"schema_version":"1.0"},"canonical_sha256":"40cb96e9c45f49129e5d722153ac29945aef55e6185c00bf2e88eb0a7429beba","source":{"kind":"arxiv","id":"2210.13686","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.13686","created_at":"2026-07-05T05:10:21Z"},{"alias_kind":"arxiv_version","alias_value":"2210.13686v1","created_at":"2026-07-05T05:10:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.13686","created_at":"2026-07-05T05:10:21Z"},{"alias_kind":"pith_short_12","alias_value":"IDFZN2OEL5ER","created_at":"2026-07-05T05:10:21Z"},{"alias_kind":"pith_short_16","alias_value":"IDFZN2OEL5ERFHS5","created_at":"2026-07-05T05:10:21Z"},{"alias_kind":"pith_short_8","alias_value":"IDFZN2OE","created_at":"2026-07-05T05:10:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:IDFZN2OEL5ERFHS5OIQVHLBJSR","target":"record","payload":{"canonical_record":{"source":{"id":"2210.13686","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-10-25T01:08:20Z","cross_cats_sorted":[],"title_canon_sha256":"0f2f26199f2e1d5918eabbfc64e00aa6e0443688a93d801970a1aff241b84d8d","abstract_canon_sha256":"01a858b9d8caf3d7ba50301b565675e4df3a6a07b0bb256b820668650c5d8d7e"},"schema_version":"1.0"},"canonical_sha256":"40cb96e9c45f49129e5d722153ac29945aef55e6185c00bf2e88eb0a7429beba","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:10:21.054852Z","signature_b64":"13g858rLjpK7v2iTWICvYDwkIvD+uy1yhzOC9C8E0ASWkKaprZ+1bqHCm7ck6ffOTDb9Ex8IOT21xQccMD/4Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"40cb96e9c45f49129e5d722153ac29945aef55e6185c00bf2e88eb0a7429beba","last_reissued_at":"2026-07-05T05:10:21.054401Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:10:21.054401Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2210.13686","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:10:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cwJBCGJjgyHFpBGSMzQnzMCxXM85uzBwkVsLp/QW/GpAo1v8VuZ/ubsBz0Knve753vlvoJfBqzZYyJBI7sWIDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T02:02:37.870886Z"},"content_sha256":"1cf3cee4210231922b21359b0dad56808571a5ac65cc9bc3c6bfb25395e31df0","schema_version":"1.0","event_id":"sha256:1cf3cee4210231922b21359b0dad56808571a5ac65cc9bc3c6bfb25395e31df0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:IDFZN2OEL5ERFHS5OIQVHLBJSR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"FedGRec: Federated Graph Recommender System with Lazy Update of Latent Embeddings","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Heng Huang, Junyi Li","submitted_at":"2022-10-25T01:08:20Z","abstract_excerpt":"Recommender systems are widely used in industry to improve user experience. Despite great success, they have recently been criticized for collecting private user data. Federated Learning (FL) is a new paradigm for learning on distributed data without direct data sharing. Therefore, Federated Recommender (FedRec) systems are proposed to mitigate privacy concerns to non-distributed recommender systems. However, FedRec systems have a performance gap to its non-distributed counterpart. The main reason is that local clients have an incomplete user-item interaction graph, thus FedRec systems cannot "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.13686","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2210.13686/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:10:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Bd6zEDIlJXNfe/ns+6kImhWENze9ZKDwPSMf8g6KfqbgdUbnhwGVCyxlZWqHNzd3otTOwnznev5elqYRpSrDBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T02:02:37.871419Z"},"content_sha256":"1f39b07220e2d291fe074467823f01aeec502de8c8e537d0494f977f2d756ede","schema_version":"1.0","event_id":"sha256:1f39b07220e2d291fe074467823f01aeec502de8c8e537d0494f977f2d756ede"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/IDFZN2OEL5ERFHS5OIQVHLBJSR/bundle.json","state_url":"https://pith.science/pith/IDFZN2OEL5ERFHS5OIQVHLBJSR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/IDFZN2OEL5ERFHS5OIQVHLBJSR/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-22T02:02:37Z","links":{"resolver":"https://pith.science/pith/IDFZN2OEL5ERFHS5OIQVHLBJSR","bundle":"https://pith.science/pith/IDFZN2OEL5ERFHS5OIQVHLBJSR/bundle.json","state":"https://pith.science/pith/IDFZN2OEL5ERFHS5OIQVHLBJSR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/IDFZN2OEL5ERFHS5OIQVHLBJSR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:IDFZN2OEL5ERFHS5OIQVHLBJSR","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":"01a858b9d8caf3d7ba50301b565675e4df3a6a07b0bb256b820668650c5d8d7e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-10-25T01:08:20Z","title_canon_sha256":"0f2f26199f2e1d5918eabbfc64e00aa6e0443688a93d801970a1aff241b84d8d"},"schema_version":"1.0","source":{"id":"2210.13686","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.13686","created_at":"2026-07-05T05:10:21Z"},{"alias_kind":"arxiv_version","alias_value":"2210.13686v1","created_at":"2026-07-05T05:10:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.13686","created_at":"2026-07-05T05:10:21Z"},{"alias_kind":"pith_short_12","alias_value":"IDFZN2OEL5ER","created_at":"2026-07-05T05:10:21Z"},{"alias_kind":"pith_short_16","alias_value":"IDFZN2OEL5ERFHS5","created_at":"2026-07-05T05:10:21Z"},{"alias_kind":"pith_short_8","alias_value":"IDFZN2OE","created_at":"2026-07-05T05:10:21Z"}],"graph_snapshots":[{"event_id":"sha256:1f39b07220e2d291fe074467823f01aeec502de8c8e537d0494f977f2d756ede","target":"graph","created_at":"2026-07-05T05:10:21Z","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/2210.13686/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recommender systems are widely used in industry to improve user experience. Despite great success, they have recently been criticized for collecting private user data. Federated Learning (FL) is a new paradigm for learning on distributed data without direct data sharing. Therefore, Federated Recommender (FedRec) systems are proposed to mitigate privacy concerns to non-distributed recommender systems. However, FedRec systems have a performance gap to its non-distributed counterpart. The main reason is that local clients have an incomplete user-item interaction graph, thus FedRec systems cannot ","authors_text":"Heng Huang, Junyi Li","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-10-25T01:08:20Z","title":"FedGRec: Federated Graph Recommender System with Lazy Update of Latent Embeddings"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.13686","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":"sha256:1cf3cee4210231922b21359b0dad56808571a5ac65cc9bc3c6bfb25395e31df0","target":"record","created_at":"2026-07-05T05:10:21Z","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":"01a858b9d8caf3d7ba50301b565675e4df3a6a07b0bb256b820668650c5d8d7e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-10-25T01:08:20Z","title_canon_sha256":"0f2f26199f2e1d5918eabbfc64e00aa6e0443688a93d801970a1aff241b84d8d"},"schema_version":"1.0","source":{"id":"2210.13686","kind":"arxiv","version":1}},"canonical_sha256":"40cb96e9c45f49129e5d722153ac29945aef55e6185c00bf2e88eb0a7429beba","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"40cb96e9c45f49129e5d722153ac29945aef55e6185c00bf2e88eb0a7429beba","first_computed_at":"2026-07-05T05:10:21.054401Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:10:21.054401Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"13g858rLjpK7v2iTWICvYDwkIvD+uy1yhzOC9C8E0ASWkKaprZ+1bqHCm7ck6ffOTDb9Ex8IOT21xQccMD/4Bg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:10:21.054852Z","signed_message":"canonical_sha256_bytes"},"source_id":"2210.13686","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1cf3cee4210231922b21359b0dad56808571a5ac65cc9bc3c6bfb25395e31df0","sha256:1f39b07220e2d291fe074467823f01aeec502de8c8e537d0494f977f2d756ede"],"state_sha256":"982a99b1a0f74a9b3695e792f4dea722080cf392d1ef1c1347d11a123d62b16e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"anWQL+PM/qLvLRo8ibOrb3Nk8xvTAI6eWmwu16ET/iVLiSUPwpQ9z2CnMH+2VnFNVC5LN7ra9HT869gOi3iuBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-22T02:02:37.875807Z","bundle_sha256":"a2f95c55eb68353d8529079c5107f6588b0e8153f37dd254318efd5c34e19009"}}