{"as_of":"2026-08-22T03:56:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4045c4224f9f57f1627b0722b061db83e1bb72d21ca0362f6d4d0b777fe13f27","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":2,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":2,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-21T06:32:19.484+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T05:50:58.778458Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-07T05:50:59.079943Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2109.05922","last_updated":"2021-09-13T12:43:00Z","snapshot_observed_at":"2026-08-16T17:57:03.092336Z","submitted_at":"2021-09-13T12:43:00Z","title":"r-GAT: Relational Graph Attention Network for Multi-Relational Graphs","version":1},"cited_work":{"arxiv_id":"2109.05922","doi":null,"metadata_source":"pith","pith_arxiv_id":"2109.05922","snapshot_observed_at":"2026-08-07T05:50:59.079943Z","title":"r-GAT: Relational Graph Attention Network for Multi-Relational Graphs","venue":"cs.AI","work_id":"f68515c6-0930-4929-be3b-142d3bfae24b","year":2021},"citing_paper":{"arxiv_id":"2506.06915","last_updated":"2025-06-07T20:29:59Z","snapshot_observed_at":"2026-08-15T02:55:29.707992Z","submitted_at":"2025-06-07T20:29:59Z","title":"Graph Neural Networks in Modern AI-aided Drug Discovery","version":1},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-07T05:50:58.778458Z"},"links":{"cited_paper":"/paper/2109.05922","citing_paper":"/paper/2506.06915"},"observation_digest":"sha256:c11a96cb3c88c2ace7333e9d65ec704835e805b1b92f45f83135d2456128e895","observation_id":"aef009cf-c2ee-4a2e-bf08-a2fed70f54e7","resolution":{"observed_at":"2026-08-07T05:50:59.083657Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2109.05922","last_updated":"2021-09-13T12:43:00Z","snapshot_observed_at":"2026-08-16T17:57:03.092336Z","submitted_at":"2021-09-13T12:43:00Z","title":"r-GAT: Relational Graph Attention Network for Multi-Relational Graphs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2109.05922","snapshot_observed_at":"2026-07-13T12:55:27.280416Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2604.03591","last_updated":"2026-04-08T18:47:10Z","snapshot_observed_at":"2026-08-15T21:02:33.396552Z","submitted_at":"2026-04-04T04:51:29Z","title":"Minos: Systematically Classifying Performance and Power Characteristics of GPU Workloads on HPC Clusters","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-07-13T12:55:27.280416Z"},"links":{"cited_paper":"/paper/2109.05922","citing_paper":"/paper/2604.03591"},"observation_digest":"sha256:4c4c3acb8721f4b7bb2a7d3dd4842880f15d814992a50dcef1997d47db59877a","observation_id":"a84c03eb-8ccf-4d62-afe2-faa240d4cb1f","resolution":{"observed_at":"2026-07-13T12:55:27.280416Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2109.05922/citation-record","integrity":"/paper/2109.05922/integrity","json":"/paper/2109.05922/citation-record.json","paper":"/paper/2109.05922"},"outbound":[],"paper":{"arxiv_id":"2109.05922","last_updated":"2021-09-13T12:43:00Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-16T17:57:03.092336Z","submitted_at":"2021-09-13T12:43:00Z","title":"r-GAT: Relational Graph Attention Network for Multi-Relational Graphs"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"thesis":"As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2109.05922."}