{"as_of":"2026-08-18T13:03:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:3a04546f95d43230b186644dfee66303590e4555030c95808935d0c9b5840c9c","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":1,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":1,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T19:12:36.558434Z","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":"2026-08-15T19:12:36.644093Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2405.10218","last_updated":"2024-05-16T16:08:49Z","snapshot_observed_at":"2026-08-17T10:37:41.174719Z","submitted_at":"2024-05-16T16:08:49Z","title":"ENADPool: The Edge-Node Attention-based Differentiable Pooling for Graph Neural Networks","version":1},"cited_work":{"arxiv_id":"2405.10218","doi":null,"metadata_source":"pith","pith_arxiv_id":"2405.10218","snapshot_observed_at":"2026-08-15T19:12:36.644093Z","title":"ENADPool: The Edge-Node Attention-based Differentiable Pooling for Graph Neural Networks","venue":"cs.LG","work_id":"c3a96f4b-11aa-4880-a077-99d6566c674b","year":2024},"citing_paper":{"arxiv_id":"2506.21612","last_updated":"2025-06-21T08:06:06Z","snapshot_observed_at":"2026-08-16T04:26:22.066588Z","submitted_at":"2025-06-21T08:06:06Z","title":"AdaptGOT: A Pre-trained Model for Adaptive Contextual POI Representation Learning","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-15T19:12:36.558434Z"},"links":{"cited_paper":"/paper/2405.10218","citing_paper":"/paper/2506.21612"},"observation_digest":"sha256:3a0887ae30a3ca9cf478f46d02bb3b8ea6b1adf9ce0b4826fbef1ae7e65b4f93","observation_id":"1f3d2159-2295-49a4-a20d-14d7016cc96f","resolution":{"observed_at":"2026-08-15T19:12:36.649813Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2405.10218/citation-record","integrity":"/paper/2405.10218/integrity","json":"/paper/2405.10218/citation-record.json","paper":"/paper/2405.10218"},"outbound":[],"paper":{"arxiv_id":"2405.10218","last_updated":"2024-05-16T16:08:49Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-17T10:37:41.174719Z","submitted_at":"2024-05-16T16:08:49Z","title":"ENADPool: The Edge-Node Attention-based Differentiable Pooling 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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2405.10218."}