{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:QFVUVZK6F4RCAVI4BB2L3BYTJH","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":"9f557eaf88b24f3917215dd9663915b3ed9f3e2373d9586ef6ee4c64a93e0c93","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-25T08:21:44Z","title_canon_sha256":"a5795ec1b8b0011188376292c4235d4b0f12d3d4839223be669b6f37f07585ad"},"schema_version":"1.0","source":{"id":"1811.09971","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.09971","created_at":"2026-05-17T23:59:58Z"},{"alias_kind":"arxiv_version","alias_value":"1811.09971v1","created_at":"2026-05-17T23:59:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.09971","created_at":"2026-05-17T23:59:58Z"},{"alias_kind":"pith_short_12","alias_value":"QFVUVZK6F4RC","created_at":"2026-05-18T12:32:46Z"},{"alias_kind":"pith_short_16","alias_value":"QFVUVZK6F4RCAVI4","created_at":"2026-05-18T12:32:46Z"},{"alias_kind":"pith_short_8","alias_value":"QFVUVZK6","created_at":"2026-05-18T12:32:46Z"}],"graph_snapshots":[{"event_id":"sha256:9dd096ff0d186dc034c36213edae5d8b5e290944a8570a3ae106000f0a6b244c","target":"graph","created_at":"2026-05-17T23:59:58Z","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":"Recently, graph Convolutional Neural Networks (graph CNNs) have been widely used for graph data representation and semi-supervised learning tasks. However, existing graph CNNs generally use a fixed graph which may be not optimal for semi-supervised learning tasks. In this paper, we propose a novel Graph Learning-Convolutional Network (GLCN) for graph data representation and semi-supervised learning. The aim of GLCN is to learn an optimal graph structure that best serves graph CNNs for semi-supervised learning by integrating both graph learning and graph convolution together in a unified networ","authors_text":"Bo Jiang, Doudou Lin, Jin Tang, Ziyan Zhang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-25T08:21:44Z","title":"Graph Learning-Convolutional Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.09971","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":"sha256:73a1d2dd60f30098a015107f4a9916af576b47acbe4778711db2ee5595ddaf48","target":"record","created_at":"2026-05-17T23:59:58Z","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":"9f557eaf88b24f3917215dd9663915b3ed9f3e2373d9586ef6ee4c64a93e0c93","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-25T08:21:44Z","title_canon_sha256":"a5795ec1b8b0011188376292c4235d4b0f12d3d4839223be669b6f37f07585ad"},"schema_version":"1.0","source":{"id":"1811.09971","kind":"arxiv","version":1}},"canonical_sha256":"816b4ae55e2f2220551c0874bd871349f409347c43ea738b7861b3f70404ab7c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"816b4ae55e2f2220551c0874bd871349f409347c43ea738b7861b3f70404ab7c","first_computed_at":"2026-05-17T23:59:58.977237Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:59:58.977237Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"e6hcvBGbmthA20eRmwN1GkYx9/bZ6z2lQiGnho87vvMYkbjmwx5drCoaQ+2owqwKp0cRffpsUakcB6ghnpFMCg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:59:58.977802Z","signed_message":"canonical_sha256_bytes"},"source_id":"1811.09971","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:73a1d2dd60f30098a015107f4a9916af576b47acbe4778711db2ee5595ddaf48","sha256:9dd096ff0d186dc034c36213edae5d8b5e290944a8570a3ae106000f0a6b244c"],"state_sha256":"de4e4ee1a71a9202b849a16e255930a61dffe7a33f77fc2e74d42bca745a929a"}