{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:2I7ZMG6H7O7W332P2N2H3ORZAL","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":"43a0d1023d7d175312d21345aa8363f4bab6543ac4eb83ade503e7a9bf9b186d","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-05T17:28:19Z","title_canon_sha256":"175e231005190578f8dfc5eb63c7b44a171bcd25556a5fea55d52d1bad152c67"},"schema_version":"1.0","source":{"id":"2606.07475","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.07475","created_at":"2026-06-08T01:05:29Z"},{"alias_kind":"arxiv_version","alias_value":"2606.07475v1","created_at":"2026-06-08T01:05:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.07475","created_at":"2026-06-08T01:05:29Z"},{"alias_kind":"pith_short_12","alias_value":"2I7ZMG6H7O7W","created_at":"2026-06-08T01:05:29Z"},{"alias_kind":"pith_short_16","alias_value":"2I7ZMG6H7O7W332P","created_at":"2026-06-08T01:05:29Z"},{"alias_kind":"pith_short_8","alias_value":"2I7ZMG6H","created_at":"2026-06-08T01:05:29Z"}],"graph_snapshots":[{"event_id":"sha256:1acd910838053a980c73281799f94ad6dffbd0302057bf9a7dab231066f63798","target":"graph","created_at":"2026-06-08T01:05:29Z","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/2606.07475/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Node classification in graph neural networks (GNNs) has been widely applied in various fields of graph analysis. GNNs achieve high-accuracy node classification in homophilous graphs, where nodes with the same class label tend to be connected. However, their performance remains limited in heterophilous graphs, where nodes with different class labels are more likely to be connected. In particular, current GNNs derived from graph convolutional networks cannot capture higher-order class label connectivity, which is frequently observed in real-world heterophilous graphs. To address this issue, we p","authors_text":"Itsuki Nakayama, Makoto Onizuka, Ryosuke Kikuchi, Takahiro Mitani, Takuto Takahashi, Yuya Sasaki","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-05T17:28:19Z","title":"Graph Neural Network leveraging Higher-order Class Label Connectivity for Heterophilous Graphs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.07475","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":"sha256:9067d956b8c9b74e75fbbc79d625e4a3c1fa7cfc6a83d796751edf17ba4ba506","target":"record","created_at":"2026-06-08T01:05:29Z","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":"43a0d1023d7d175312d21345aa8363f4bab6543ac4eb83ade503e7a9bf9b186d","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-05T17:28:19Z","title_canon_sha256":"175e231005190578f8dfc5eb63c7b44a171bcd25556a5fea55d52d1bad152c67"},"schema_version":"1.0","source":{"id":"2606.07475","kind":"arxiv","version":1}},"canonical_sha256":"d23f961bc7fbbf6def4fd3747dba3902c7d56e3c5116a2716cb00506e372e5b2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d23f961bc7fbbf6def4fd3747dba3902c7d56e3c5116a2716cb00506e372e5b2","first_computed_at":"2026-06-08T01:05:29.304350Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-08T01:05:29.304350Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"PGIAkW1tavRoEZavQYLdohcOzKqSwa3I1QfJwKBFIj9UnkAjq54eEJQxIa/QerVsWoOICQ8mJgjoTcP1eOkADg==","signature_status":"signed_v1","signed_at":"2026-06-08T01:05:29.305240Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.07475","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9067d956b8c9b74e75fbbc79d625e4a3c1fa7cfc6a83d796751edf17ba4ba506","sha256:1acd910838053a980c73281799f94ad6dffbd0302057bf9a7dab231066f63798"],"state_sha256":"18d07dbde6dcb1219ba1c2e55dcb0785375d294adf34dccb7d88ec9f9e33d680"}