{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:3BR36P6IVH747DCL2FVP3BH3LO","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":"7847ca024169e7afc4eb11bf2878d5fea58d2293ad1be308da4b3da0cfe05613","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-05T21:39:59Z","title_canon_sha256":"42e7c16ced27f58f4e43931fd67ab74ade88fd99249400bf735ae564cf593802"},"schema_version":"1.0","source":{"id":"1906.02319","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.02319","created_at":"2026-05-17T23:44:01Z"},{"alias_kind":"arxiv_version","alias_value":"1906.02319v1","created_at":"2026-05-17T23:44:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.02319","created_at":"2026-05-17T23:44:01Z"},{"alias_kind":"pith_short_12","alias_value":"3BR36P6IVH74","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_16","alias_value":"3BR36P6IVH747DCL","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_8","alias_value":"3BR36P6I","created_at":"2026-05-18T12:33:07Z"}],"graph_snapshots":[{"event_id":"sha256:04acc16798ac8e14a483afb4846ee6d07cce4699163f5e6260dab1f293dc9346","target":"graph","created_at":"2026-05-17T23:44:01Z","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"},"paper":{"abstract_excerpt":"Graph data widely exist in many high-impact applications. Inspired by the success of deep learning in grid-structured data, graph neural network models have been proposed to learn powerful node-level or graph-level representation. However, most of the existing graph neural networks suffer from the following limitations: (1) there is limited analysis regarding the graph convolution properties, such as seed-oriented, degree-aware and order-free; (2) the node's degree-specific graph structure is not explicitly expressed in graph convolution for distinguishing structure-aware node neighborhoods; (","authors_text":"Jiejun Xu, Jingrui He, Jun Wu","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-05T21:39:59Z","title":"DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.02319","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":"sha256:60fb120eb6c2b8b316524573da68155030745519ef8fa7d724ad49d15ef81313","target":"record","created_at":"2026-05-17T23:44:01Z","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":"7847ca024169e7afc4eb11bf2878d5fea58d2293ad1be308da4b3da0cfe05613","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-05T21:39:59Z","title_canon_sha256":"42e7c16ced27f58f4e43931fd67ab74ade88fd99249400bf735ae564cf593802"},"schema_version":"1.0","source":{"id":"1906.02319","kind":"arxiv","version":1}},"canonical_sha256":"d863bf3fc8a9ffcf8c4bd16afd84fb5ba810d10b0f37c0ba167a19f82f978028","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d863bf3fc8a9ffcf8c4bd16afd84fb5ba810d10b0f37c0ba167a19f82f978028","first_computed_at":"2026-05-17T23:44:01.597275Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:44:01.597275Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"yMRUm3VMj1Bs9BeZkMRpqEZIxh2ddjTEaKIRik93B3a8Cj9moZdTr7IGXsA6t+usiGRdkItuzDIY3R+Yd2vuBQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:44:01.597845Z","signed_message":"canonical_sha256_bytes"},"source_id":"1906.02319","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:60fb120eb6c2b8b316524573da68155030745519ef8fa7d724ad49d15ef81313","sha256:04acc16798ac8e14a483afb4846ee6d07cce4699163f5e6260dab1f293dc9346"],"state_sha256":"7eab0c9270fa6d3e5b978176e4e067c6cc521f32b6f2e41b81263c1a27d3d411"}