{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:RYO6KVG4ZCYIIYP24NGE7FIUNO","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":"0a97e9dbfa0440fe0159772ee8b0c0c648438499be72d81de011c9df19dcea32","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-05-04T07:53:16Z","title_canon_sha256":"5029744ddc46a3948cc10d80d3d50bcbe095be0739982f4a5c761eddaf58ea66"},"schema_version":"1.0","source":{"id":"2505.02020","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.02020","created_at":"2026-07-05T10:58:30Z"},{"alias_kind":"arxiv_version","alias_value":"2505.02020v1","created_at":"2026-07-05T10:58:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.02020","created_at":"2026-07-05T10:58:30Z"},{"alias_kind":"pith_short_12","alias_value":"RYO6KVG4ZCYI","created_at":"2026-07-05T10:58:30Z"},{"alias_kind":"pith_short_16","alias_value":"RYO6KVG4ZCYIIYP2","created_at":"2026-07-05T10:58:30Z"},{"alias_kind":"pith_short_8","alias_value":"RYO6KVG4","created_at":"2026-07-05T10:58:30Z"}],"graph_snapshots":[{"event_id":"sha256:ecabaad894f4204298e0b401389e0a49daa2020b3649781b5ee5dc47ca59f032","target":"graph","created_at":"2026-07-05T10:58:30Z","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/2505.02020/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Wide & Deep, a simple yet effective learning architecture for recommendation systems developed by Google, has had a significant impact in both academia and industry due to its combination of the memorization ability of generalized linear models and the generalization ability of deep models. Graph convolutional networks (GCNs) remain dominant in node classification tasks; however, recent studies have highlighted issues such as heterophily and expressiveness, which focus on graph structure while seemingly neglecting the potential role of node features. In this paper, we propose a flexible framew","authors_text":"Wenguo Yang, Yancheng Chen, Zhipeng Jiang","cross_cats":["cs.AI","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-05-04T07:53:16Z","title":"Wide & Deep Learning for Node Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.02020","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":"sha256:2b2cc85f95179762629e81c95e8d76d9ccba042c1ef617f47cf1a1d510387b2e","target":"record","created_at":"2026-07-05T10:58:30Z","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":"0a97e9dbfa0440fe0159772ee8b0c0c648438499be72d81de011c9df19dcea32","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-05-04T07:53:16Z","title_canon_sha256":"5029744ddc46a3948cc10d80d3d50bcbe095be0739982f4a5c761eddaf58ea66"},"schema_version":"1.0","source":{"id":"2505.02020","kind":"arxiv","version":1}},"canonical_sha256":"8e1de554dcc8b08461fae34c4f95146bb7145c320393661a95e0b4a7a4333176","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8e1de554dcc8b08461fae34c4f95146bb7145c320393661a95e0b4a7a4333176","first_computed_at":"2026-07-05T10:58:30.563551Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:58:30.563551Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"p7bp+A2YaMhYzslNyF6WAZghg2kRqt+6nlbMI3W0DtBsvfNvgnrNJ52EA11NaMqG/WTh5MFTo7p/GfPEZXm0Cg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:58:30.564248Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.02020","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2b2cc85f95179762629e81c95e8d76d9ccba042c1ef617f47cf1a1d510387b2e","sha256:ecabaad894f4204298e0b401389e0a49daa2020b3649781b5ee5dc47ca59f032"],"state_sha256":"2a12006344a05196d02336078f165c019628a029bb482038f4f801f5e8136209"}