{"as_of":"2026-08-20T20:21:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e831e169f9390d76ca08cbf74d56646661b6c4f19749ea47b6b909717e259d8a","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":3,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":3,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-20T06:33:59.587034+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T22:29:31.657139Z","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":"2026-07-04T03:49:30.662836Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2203.17159","last_updated":"2022-11-02T14:37:26Z","snapshot_observed_at":"2026-08-16T17:10:12.244548Z","submitted_at":"2022-03-31T16:33:31Z","title":"Preventing Over-Smoothing for Hypergraph Neural Networks","version":2},"cited_work":{"arxiv_id":"2203.17159","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2203.17159","snapshot_observed_at":"2026-07-04T03:49:30.662836Z","title":"Preventing over-smoothing for hypergraph neural networks","venue":null,"work_id":"4122b73d-92f0-40fb-9ab9-5597aebaddeb","year":2022},"citing_paper":{"arxiv_id":"2604.10955","last_updated":"2026-04-13T03:52:01Z","snapshot_observed_at":"2026-08-13T11:15:39.797453Z","submitted_at":"2026-04-13T03:52:01Z","title":"Hypergraph Neural Diffusion: A PDE-Inspired Framework for Hypergraph Message Passing","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-05-10T16:19:24.765498Z"},"links":{"cited_paper":"/paper/2203.17159","citing_paper":"/paper/2604.10955"},"observation_digest":"sha256:29c9131bdafb77e3bda673cf91ecbf9560872751922462856c79a83b5fdcefda","observation_id":"d4cdb763-5757-45ff-b280-a179bafa21d6","resolution":{"observed_at":"2026-05-11T09:01:00.037165Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2203.17159","last_updated":"2022-11-02T14:37:26Z","snapshot_observed_at":"2026-08-16T17:10:12.244548Z","submitted_at":"2022-03-31T16:33:31Z","title":"Preventing Over-Smoothing for Hypergraph Neural Networks","version":2},"cited_work":{"arxiv_id":"2203.17159","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2203.17159","snapshot_observed_at":"2026-07-04T03:49:30.662836Z","title":"Preventing over-smoothing for hypergraph neural networks","venue":null,"work_id":"4122b73d-92f0-40fb-9ab9-5597aebaddeb","year":2022},"citing_paper":{"arxiv_id":"2606.20162","last_updated":"2026-06-18T12:28:30Z","snapshot_observed_at":"2026-08-15T07:19:39.200838Z","submitted_at":"2026-06-18T12:28:30Z","title":"Implicit Semantic-Aware Communication Based on Hypergraph Reasoning","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-06-26T17:36:09.356083Z"},"links":{"cited_paper":"/paper/2203.17159","citing_paper":"/paper/2606.20162"},"observation_digest":"sha256:fd947e9e8dd1489a980ef8d14faed937b1a3dfc89d1019d59c3cf40fff8ab898","observation_id":"ac3fce0e-af2c-4b70-8c10-852ff9c879c1","resolution":{"observed_at":"2026-07-04T03:49:30.664684Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2203.17159","last_updated":"2022-11-02T14:37:26Z","snapshot_observed_at":"2026-08-16T17:10:12.244548Z","submitted_at":"2022-03-31T16:33:31Z","title":"Preventing Over-Smoothing for Hypergraph Neural Networks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.17159","snapshot_observed_at":"2026-08-01T22:29:31.657139Z","title":"Preventing over-smoothing for hypergraph neural networks,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.15773","last_updated":"2026-07-17T09:04:22Z","snapshot_observed_at":"2026-08-16T02:11:06.535300Z","submitted_at":"2026-07-17T09:04:22Z","title":"From Diffusion to Reaction-Diffusion: A Dynamical-Systems View of Oversmoothing in Hypergraph Neural Networks","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-01T22:29:31.657139Z"},"links":{"cited_paper":"/paper/2203.17159","citing_paper":"/paper/2607.15773"},"observation_digest":"sha256:03912ef22b6debbddb5806219e2f0b91b73c53af8e6f914a205f8bc28afaa499","observation_id":"e3524fd2-69ef-40e9-bad1-98ef3b4dbe5d","resolution":{"observed_at":"2026-08-01T22:29:31.657139Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2203.17159/citation-record","integrity":"/paper/2203.17159/integrity","json":"/paper/2203.17159/citation-record.json","paper":"/paper/2203.17159"},"outbound":[],"paper":{"arxiv_id":"2203.17159","last_updated":"2022-11-02T14:37:26Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-16T17:10:12.244548Z","submitted_at":"2022-03-31T16:33:31Z","title":"Preventing Over-Smoothing for Hypergraph 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":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"thesis":"As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2203.17159."}