{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:IKDFQTCXKWMNZEFZRFDNL6EEVO","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":"44cc5d121d08573b86b26f8f260504d40a00e269570f32687cc327a1fdb34007","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-26T14:21:21Z","title_canon_sha256":"2f6e5a30820e4c8392cf88561bf2615fd3edcf8d254b5c191424ba56c06d0753"},"schema_version":"1.0","source":{"id":"2406.18380","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.18380","created_at":"2026-07-05T10:25:07Z"},{"alias_kind":"arxiv_version","alias_value":"2406.18380v4","created_at":"2026-07-05T10:25:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.18380","created_at":"2026-07-05T10:25:07Z"},{"alias_kind":"pith_short_12","alias_value":"IKDFQTCXKWMN","created_at":"2026-07-05T10:25:07Z"},{"alias_kind":"pith_short_16","alias_value":"IKDFQTCXKWMNZEFZ","created_at":"2026-07-05T10:25:07Z"},{"alias_kind":"pith_short_8","alias_value":"IKDFQTCX","created_at":"2026-07-05T10:25:07Z"}],"graph_snapshots":[{"event_id":"sha256:463e327c7f6fe4290587d77722af21ff876452cb9d60e1d0ebe7170236a8b7cd","target":"graph","created_at":"2026-07-05T10:25:07Z","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/2406.18380/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In recent years, Graph Neural Networks (GNNs) have become the de facto tool for learning node and graph representations. Most GNNs typically consist of a sequence of neighborhood aggregation (a.k.a., message-passing) layers, within which the representation of each node is updated based on those of its neighbors. The most expressive message-passing GNNs can be obtained through the use of the sum aggregator and of MLPs for feature transformation, thanks to their universal approximation capabilities. However, the limitations of MLPs recently motivated the introduction of another family of univers","authors_text":"George Panagopoulos, Giannis Nikolentzos, Jun Pang, Michail Chatzianastasis, Michalis Vazirgiannis, Roman Bresson","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-26T14:21:21Z","title":"KAGNNs: Kolmogorov-Arnold Networks meet Graph Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.18380","kind":"arxiv","version":4},"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":"sha256:568aab16e55bb3cd41952c359a3cbd400956c64a880447f4b7d6a53fee39c23c","target":"record","created_at":"2026-07-05T10:25:07Z","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":"44cc5d121d08573b86b26f8f260504d40a00e269570f32687cc327a1fdb34007","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-26T14:21:21Z","title_canon_sha256":"2f6e5a30820e4c8392cf88561bf2615fd3edcf8d254b5c191424ba56c06d0753"},"schema_version":"1.0","source":{"id":"2406.18380","kind":"arxiv","version":4}},"canonical_sha256":"4286584c575598dc90b98946d5f884abbd5f258b85f7f5a3716ffa2f6838a776","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4286584c575598dc90b98946d5f884abbd5f258b85f7f5a3716ffa2f6838a776","first_computed_at":"2026-07-05T10:25:07.745405Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:25:07.745405Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"SAmU8Jdsusut50Z8BEIbDl4oq4LLQLRJ2ZG+KT9qs5kePt1meqXAQ1u+6D6S7jizq+KpMlZyFoL4gHRGH5JfAA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:25:07.745928Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.18380","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:568aab16e55bb3cd41952c359a3cbd400956c64a880447f4b7d6a53fee39c23c","sha256:463e327c7f6fe4290587d77722af21ff876452cb9d60e1d0ebe7170236a8b7cd"],"state_sha256":"068e2137e5d9ddc9671aebca4f7b3221a083fb2e1dce640cdd360041bffcefd7"}