{"as_of":"2026-08-10T09:20:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:fc1d76a90ecbeb8393adcb78183ed9d2db38f597ae1348aeca8a59c6124a426f","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":"2026-08-10T06:31:04.303077+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":"2026-08-05T16:00:51.673184Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-13T05:57:22.379145Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2401.09125","last_updated":"2024-06-04T14:15:55Z","snapshot_observed_at":"2026-08-03T08:14:16.445610Z","submitted_at":"2024-01-17T11:01:28Z","title":"Understanding Heterophily for Graph Neural Networks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.09125","snapshot_observed_at":"2026-08-05T16:00:51.673184Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.19071","last_updated":"2025-08-28T09:15:01Z","snapshot_observed_at":"2026-08-09T08:52:28.944600Z","submitted_at":"2025-08-26T14:28:31Z","title":"Dynamic Triangulation-Based Graph Rewiring for Graph Neural Networks","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-05T16:00:51.673184Z"},"links":{"cited_paper":"/paper/2401.09125","citing_paper":"/paper/2508.19071"},"observation_digest":"sha256:6e034d37931e7dfffc2db058d5389ff09cf0b1d7b71d51120bc4cb487b116986","observation_id":"15612f42-b4b7-4387-8b13-ff1e14f5d3e5","resolution":{"observed_at":"2026-08-05T16:00:51.673184Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.09125","last_updated":"2024-06-04T14:15:55Z","snapshot_observed_at":"2026-08-03T08:14:16.445610Z","submitted_at":"2024-01-17T11:01:28Z","title":"Understanding Heterophily for Graph Neural Networks","version":2},"cited_work":{"arxiv_id":"2401.09125","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2401.09125","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Understanding heterophily for graph neural net- works.arXiv preprint arXiv:2401.09125","venue":null,"work_id":"6b02da32-64a9-4546-a934-94a3d3f6c2e3","year":null},"citing_paper":{"arxiv_id":"2605.10975","last_updated":"2026-05-08T22:35:17Z","snapshot_observed_at":"2026-07-06T23:22:52.369277Z","submitted_at":"2026-05-08T22:35:17Z","title":"Hierarchical Multi-Scale Graph Neural Networks: Scalable Heterophilous Learning with Oversmoothing and Oversquashing Mitigation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-13T05:57:17.440810Z"},"links":{"cited_paper":"/paper/2401.09125","citing_paper":"/paper/2605.10975"},"observation_digest":"sha256:7604ff678be8e7eef4b1dbcbe1a273c34fefaa807cda02113b7183bf1392c225","observation_id":"1d1308a0-77db-4524-912c-1331c5ed545d","resolution":{"observed_at":"2026-05-13T05:57:22.380738Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2401.09125/citation-record","integrity":"/paper/2401.09125/integrity","json":"/paper/2401.09125/citation-record.json","paper":"/paper/2401.09125"},"outbound":[],"paper":{"arxiv_id":"2401.09125","last_updated":"2024-06-04T14:15:55Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-03T08:14:16.445610Z","submitted_at":"2024-01-17T11:01:28Z","title":"Understanding Heterophily for Graph Neural Networks"},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2401.09125."}