{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:CX47UCSHMOEMIKENG6NPHOI2FH","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":"4943630ff1574db15c82d24315464e0faa14b22b4efa2b4e4b4cee9c42132407","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2024-01-26T15:23:25Z","title_canon_sha256":"f0dc6c904f5a86e6018ad7ab8103103e9101a1c34c05f1934b1a796ef53d44a8"},"schema_version":"1.0","source":{"id":"2401.14939","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.14939","created_at":"2026-07-05T08:16:46Z"},{"alias_kind":"arxiv_version","alias_value":"2401.14939v2","created_at":"2026-07-05T08:16:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.14939","created_at":"2026-07-05T08:16:46Z"},{"alias_kind":"pith_short_12","alias_value":"CX47UCSHMOEM","created_at":"2026-07-05T08:16:46Z"},{"alias_kind":"pith_short_16","alias_value":"CX47UCSHMOEMIKEN","created_at":"2026-07-05T08:16:46Z"},{"alias_kind":"pith_short_8","alias_value":"CX47UCSH","created_at":"2026-07-05T08:16:46Z"}],"graph_snapshots":[{"event_id":"sha256:a576469106d5a451a307abefa810d06eeafed294533c68177911af89cbf9c96b","target":"graph","created_at":"2026-07-05T08:16:46Z","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/2401.14939/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Predicting Click-Through Rate (CTR) in billion-scale recommender systems poses a long-standing challenge for Graph Neural Networks (GNNs) due to the overwhelming computational complexity involved in aggregating billions of neighbors. To tackle this, GNN-based CTR models usually sample hundreds of neighbors out of the billions to facilitate efficient online recommendations. However, sampling only a small portion of neighbors results in a severe sampling bias and the failure to encompass the full spectrum of user or item behavioral patterns. To address this challenge, we name the conventional us","authors_text":"Feiran Huang, Hao Chen, Qijie Shen, Senzhang Wang, Sheng Zhou, Wenbing Huang, Xiao Huang, Yuanchen Bei, Yue Xu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2024-01-26T15:23:25Z","title":"Macro Graph Neural Networks for Online Billion-Scale Recommender Systems"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.14939","kind":"arxiv","version":2},"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":"sha256:2b39d3ad33eb45af24531a3089e06c8d635d8c1848bac7017f3697cafbe36c85","target":"record","created_at":"2026-07-05T08:16:46Z","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":"4943630ff1574db15c82d24315464e0faa14b22b4efa2b4e4b4cee9c42132407","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2024-01-26T15:23:25Z","title_canon_sha256":"f0dc6c904f5a86e6018ad7ab8103103e9101a1c34c05f1934b1a796ef53d44a8"},"schema_version":"1.0","source":{"id":"2401.14939","kind":"arxiv","version":2}},"canonical_sha256":"15f9fa0a476388c4288d379af3b91a29c7582cb8073fb17f093ca6ab28f943cf","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"15f9fa0a476388c4288d379af3b91a29c7582cb8073fb17f093ca6ab28f943cf","first_computed_at":"2026-07-05T08:16:46.685915Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:16:46.685915Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KaGv/smulw6nFx0u/LdN/gyrk1ipcu6xRWBlknMcw/0UUBMKTioDPQYUnaEI6xPNFW6J3wdmoOP4/C6yRidlAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:16:46.686567Z","signed_message":"canonical_sha256_bytes"},"source_id":"2401.14939","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2b39d3ad33eb45af24531a3089e06c8d635d8c1848bac7017f3697cafbe36c85","sha256:a576469106d5a451a307abefa810d06eeafed294533c68177911af89cbf9c96b"],"state_sha256":"a1f28defd18a94e371eb6b6e1f7f585605f30e82c2e49b805ae0ba8665e03145"}