{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:5IMELN363Y4PDBRU6RJWJL2AT6","short_pith_number":"pith:5IMELN36","schema_version":"1.0","canonical_sha256":"ea1845b77ede38f18634f45364af409fbca9dcf37522d2b7f775c72f7958ba30","source":{"kind":"arxiv","id":"2303.01926","version":2},"attestation_state":"computed","paper":{"title":"RAFEN -- Regularized Alignment Framework for Embeddings of Nodes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Jakub Binkowski, Kamil Tagowski, Piotr Bielak, Tomasz Kajdanowicz","submitted_at":"2023-03-03T13:51:17Z","abstract_excerpt":"Learning representations of nodes has been a crucial area of the graph machine learning research area. A well-defined node embedding model should reflect both node features and the graph structure in the final embedding. In the case of dynamic graphs, this problem becomes even more complex as both features and structure may change over time. The embeddings of particular nodes should remain comparable during the evolution of the graph, what can be achieved by applying an alignment procedure. This step was often applied in existing works after the node embedding was already computed. In this pap"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2303.01926","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-03-03T13:51:17Z","cross_cats_sorted":[],"title_canon_sha256":"57198e84e2a185f561ead619f1965bdc8e55bea47d0c6781d89723c8879d2480","abstract_canon_sha256":"5d4e2421b2231f94b945e60533591b263e2db75be622f46db820dbdc543689db"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:02:32.711770Z","signature_b64":"pTemuNanBoe6wNxAVH0JUvpz2HgeuwKGzKIKnURIo4TxFsSGfpITHKAAsvxRt7PlyKeHT4gVAjpZ3l9X3cvJCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ea1845b77ede38f18634f45364af409fbca9dcf37522d2b7f775c72f7958ba30","last_reissued_at":"2026-07-05T06:02:32.711239Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:02:32.711239Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"RAFEN -- Regularized Alignment Framework for Embeddings of Nodes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Jakub Binkowski, Kamil Tagowski, Piotr Bielak, Tomasz Kajdanowicz","submitted_at":"2023-03-03T13:51:17Z","abstract_excerpt":"Learning representations of nodes has been a crucial area of the graph machine learning research area. A well-defined node embedding model should reflect both node features and the graph structure in the final embedding. In the case of dynamic graphs, this problem becomes even more complex as both features and structure may change over time. The embeddings of particular nodes should remain comparable during the evolution of the graph, what can be achieved by applying an alignment procedure. This step was often applied in existing works after the node embedding was already computed. In this pap"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.01926","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2303.01926/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2303.01926","created_at":"2026-07-05T06:02:32.711307+00:00"},{"alias_kind":"arxiv_version","alias_value":"2303.01926v2","created_at":"2026-07-05T06:02:32.711307+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.01926","created_at":"2026-07-05T06:02:32.711307+00:00"},{"alias_kind":"pith_short_12","alias_value":"5IMELN363Y4P","created_at":"2026-07-05T06:02:32.711307+00:00"},{"alias_kind":"pith_short_16","alias_value":"5IMELN363Y4PDBRU","created_at":"2026-07-05T06:02:32.711307+00:00"},{"alias_kind":"pith_short_8","alias_value":"5IMELN36","created_at":"2026-07-05T06:02:32.711307+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/5IMELN363Y4PDBRU6RJWJL2AT6","json":"https://pith.science/pith/5IMELN363Y4PDBRU6RJWJL2AT6.json","graph_json":"https://pith.science/api/pith-number/5IMELN363Y4PDBRU6RJWJL2AT6/graph.json","events_json":"https://pith.science/api/pith-number/5IMELN363Y4PDBRU6RJWJL2AT6/events.json","paper":"https://pith.science/paper/5IMELN36"},"agent_actions":{"view_html":"https://pith.science/pith/5IMELN363Y4PDBRU6RJWJL2AT6","download_json":"https://pith.science/pith/5IMELN363Y4PDBRU6RJWJL2AT6.json","view_paper":"https://pith.science/paper/5IMELN36","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2303.01926&json=true","fetch_graph":"https://pith.science/api/pith-number/5IMELN363Y4PDBRU6RJWJL2AT6/graph.json","fetch_events":"https://pith.science/api/pith-number/5IMELN363Y4PDBRU6RJWJL2AT6/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/5IMELN363Y4PDBRU6RJWJL2AT6/action/timestamp_anchor","attest_storage":"https://pith.science/pith/5IMELN363Y4PDBRU6RJWJL2AT6/action/storage_attestation","attest_author":"https://pith.science/pith/5IMELN363Y4PDBRU6RJWJL2AT6/action/author_attestation","sign_citation":"https://pith.science/pith/5IMELN363Y4PDBRU6RJWJL2AT6/action/citation_signature","submit_replication":"https://pith.science/pith/5IMELN363Y4PDBRU6RJWJL2AT6/action/replication_record"}},"created_at":"2026-07-05T06:02:32.711307+00:00","updated_at":"2026-07-05T06:02:32.711307+00:00"}