{"as_of":"2026-08-11T17:46:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:47bb36cd436c38cfd5bb0d3a2cdeadf016ed516d0a0119ddafa41b1a5867ffdf","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":"2026-08-11T06:34:44.6726+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":"2026-08-10T16:57:29.146615Z","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":"2026-08-07T12:57:37.106491Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2405.01009","last_updated":"2025-02-28T10:37:29Z","snapshot_observed_at":"2026-08-09T20:12:48.190458Z","submitted_at":"2024-05-02T05:23:58Z","title":"On Oversquashing in Graph Neural Networks Through the Lens of Dynamical Systems","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.01009","snapshot_observed_at":"2026-08-10T16:57:29.146615Z","title":"Tackling Oversquashing by Global and Local Non-Dissipativity","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.12732","last_updated":"2025-01-22T09:09:17Z","snapshot_observed_at":"2026-08-10T23:35:59.528749Z","submitted_at":"2025-01-22T09:09:17Z","title":"GRAMA: Adaptive Graph Autoregressive Moving Average Models","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-10T16:57:29.146615Z"},"links":{"cited_paper":"/paper/2405.01009","citing_paper":"/paper/2501.12732"},"observation_digest":"sha256:3ef55bcc9356f9803d431e8b4938cb9973670a99098467e8e6a5d5590dd43b6b","observation_id":"86dde8b2-1ef1-45b0-bd6d-d02a8c0fcc90","resolution":{"observed_at":"2026-08-10T16:57:29.146615Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.01009","last_updated":"2025-02-28T10:37:29Z","snapshot_observed_at":"2026-08-09T20:12:48.190458Z","submitted_at":"2024-05-02T05:23:58Z","title":"On Oversquashing in Graph Neural Networks Through the Lens of Dynamical Systems","version":2},"cited_work":{"arxiv_id":"2405.01009","doi":null,"metadata_source":"pith","pith_arxiv_id":"2405.01009","snapshot_observed_at":"2026-08-07T12:57:37.106491Z","title":"On Oversquashing in Graph Neural Networks Through the Lens of Dynamical Systems","venue":"cs.LG","work_id":"c3439e3b-d178-412d-b7bb-3c5bec3df459","year":2024},"citing_paper":{"arxiv_id":"2505.23185","last_updated":"2025-05-29T07:23:07Z","snapshot_observed_at":"2026-08-10T02:14:05.532165Z","submitted_at":"2025-05-29T07:23:07Z","title":"Improving the Effective Receptive Field of Message-Passing Neural Networks","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-07T12:57:33.592594Z"},"links":{"cited_paper":"/paper/2405.01009","citing_paper":"/paper/2505.23185"},"observation_digest":"sha256:3ced57f394da4cebf93e5600bc247a41856b2abe4718e0434c9c99794e54e754","observation_id":"3e80009f-dc6a-4ee4-93e1-9be07c5a40fb","resolution":{"observed_at":"2026-08-07T12:57:37.139727Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2405.01009/citation-record","integrity":"/paper/2405.01009/integrity","json":"/paper/2405.01009/citation-record.json","paper":"/paper/2405.01009"},"outbound":[],"paper":{"arxiv_id":"2405.01009","last_updated":"2025-02-28T10:37:29Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-09T20:12:48.190458Z","submitted_at":"2024-05-02T05:23:58Z","title":"On Oversquashing in Graph Neural Networks Through the Lens of Dynamical Systems"},"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":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2405.01009."}