{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:ZRKIJQRYNY2QVBVIGFA2LH3YLY","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":"50eb02fb69677346ca557c25da00a370917cd579b2de7d974c22f2af052bf7bc","cross_cats_sorted":["cs.SI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-08-18T12:49:57Z","title_canon_sha256":"f904eb61a7fca866b1d3488b7ec4705c202617231d06a9aecd434abe21892a6e"},"schema_version":"1.0","source":{"id":"2308.09517","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.09517","created_at":"2026-07-05T06:42:34Z"},{"alias_kind":"arxiv_version","alias_value":"2308.09517v1","created_at":"2026-07-05T06:42:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.09517","created_at":"2026-07-05T06:42:34Z"},{"alias_kind":"pith_short_12","alias_value":"ZRKIJQRYNY2Q","created_at":"2026-07-05T06:42:34Z"},{"alias_kind":"pith_short_16","alias_value":"ZRKIJQRYNY2QVBVI","created_at":"2026-07-05T06:42:34Z"},{"alias_kind":"pith_short_8","alias_value":"ZRKIJQRY","created_at":"2026-07-05T06:42:34Z"}],"graph_snapshots":[{"event_id":"sha256:e280954c12c71868e2d2ebd220f1bce43539873eb4bd9228b79b3f522c5ff66c","target":"graph","created_at":"2026-07-05T06:42:34Z","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/2308.09517/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Graph representation learning (GRL) methods, such as graph neural networks and graph transformer models, have been successfully used to analyze graph-structured data, mainly focusing on node classification and link prediction tasks. However, the existing studies mostly only consider local connectivity while ignoring long-range connectivity and the roles of nodes. In this paper, we propose Unified Graph Transformer Networks (UGT) that effectively integrate local and global structural information into fixed-length vector representations. First, UGT learns local structure by identifying the local","authors_text":"O-Joun Lee, Van Thuy Hoang","cross_cats":["cs.SI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-08-18T12:49:57Z","title":"Transitivity-Preserving Graph Representation Learning for Bridging Local Connectivity and Role-based Similarity"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.09517","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":"sha256:28b2aa5b1a7a31ff977fb3b6715f42f345c216551a2d8f0f9fc53e7e90c2977f","target":"record","created_at":"2026-07-05T06:42:34Z","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":"50eb02fb69677346ca557c25da00a370917cd579b2de7d974c22f2af052bf7bc","cross_cats_sorted":["cs.SI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-08-18T12:49:57Z","title_canon_sha256":"f904eb61a7fca866b1d3488b7ec4705c202617231d06a9aecd434abe21892a6e"},"schema_version":"1.0","source":{"id":"2308.09517","kind":"arxiv","version":1}},"canonical_sha256":"cc5484c2386e350a86a83141a59f785e18f6e437fab8cc4fe5d9f13c6694fce4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cc5484c2386e350a86a83141a59f785e18f6e437fab8cc4fe5d9f13c6694fce4","first_computed_at":"2026-07-05T06:42:34.111852Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:42:34.111852Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"UB9tvFQYRvTLp4myW70BR9BfPoPWO7DMWhWCswHrIK9TFBZlBML4L3SDIa+CWvaBzEhQe36Hb4P9yfwJPNDABA==","signature_status":"signed_v1","signed_at":"2026-07-05T06:42:34.112198Z","signed_message":"canonical_sha256_bytes"},"source_id":"2308.09517","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:28b2aa5b1a7a31ff977fb3b6715f42f345c216551a2d8f0f9fc53e7e90c2977f","sha256:e280954c12c71868e2d2ebd220f1bce43539873eb4bd9228b79b3f522c5ff66c"],"state_sha256":"d68da72aad8d23fc97c331c2c69cf81502cd3150f8b3674b8af93c2005b457b9"}