{"as_of":"2026-08-11T16:39:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:aa3956c33e2fee4fb0e5466f9bbfea0c46fe6184302cf720d2922139955d7ae3","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":"2026-08-11T06:34:44.6726+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":"2026-08-07T11:24:38.110006Z","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":"2026-07-03T01:17:30.943406Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2307.00495","last_updated":"2024-06-18T14:11:01Z","snapshot_observed_at":"2026-08-09T01:24:56.873715Z","submitted_at":"2023-07-02T06:56:52Z","title":"STG4Traffic: A Survey and Benchmark of Spatial-Temporal Graph Neural Networks for Traffic Prediction","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.00495","snapshot_observed_at":"2026-08-07T11:24:38.110006Z","title":"Stg4traffic: A survey and bench- mark of spatial-temporal graph neural networks for traffic prediction.CoRR, abs/2307.00495,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.02576","last_updated":"2025-06-05T07:54:37Z","snapshot_observed_at":"2026-08-10T15:48:35.746585Z","submitted_at":"2025-06-03T07:55:51Z","title":"ADFormer: Aggregation Differential Transformer for Passenger Demand Forecasting","version":3},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T11:24:38.110006Z"},"links":{"cited_paper":"/paper/2307.00495","citing_paper":"/paper/2506.02576"},"observation_digest":"sha256:808f0bdd5c16cd816dad36c04dfe850fceb6084d522099e0844497640618f77f","observation_id":"d31d25ec-6639-4ad5-becb-9a1b5cc76ff0","resolution":{"observed_at":"2026-08-07T11:24:38.110006Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.00495","last_updated":"2024-06-18T14:11:01Z","snapshot_observed_at":"2026-08-09T01:24:56.873715Z","submitted_at":"2023-07-02T06:56:52Z","title":"STG4Traffic: A Survey and Benchmark of Spatial-Temporal Graph Neural Networks for Traffic Prediction","version":2},"cited_work":{"arxiv_id":"2307.00495","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2307.00495","snapshot_observed_at":"2026-07-03T01:17:30.943406Z","title":"Stg4traffic: A survey and bench- mark of spatial-temporal graph neural networks for traffic prediction,","venue":null,"work_id":"e08916f2-b151-4f8b-a399-b37f12930f56","year":2023},"citing_paper":{"arxiv_id":"2606.09392","last_updated":"2026-06-08T12:07:13Z","snapshot_observed_at":"2026-07-06T23:48:44.159537Z","submitted_at":"2026-06-08T12:07:13Z","title":"From Coarse to Fine: Managing Temporal Granularity in Spatio-Temporal Data for Fine-Grained Traffic Prediction","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-06-27T16:40:14.247942Z"},"links":{"cited_paper":"/paper/2307.00495","citing_paper":"/paper/2606.09392"},"observation_digest":"sha256:f069b4bc483ec207e251449c08effceed86d3ccffe7bdeca0301cbd4aae0c5ce","observation_id":"819120ae-877b-472a-88ee-eceedf331866","resolution":{"observed_at":"2026-07-03T01:17:30.944979Z","resolver_source":"arxiv_id","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"}},{"citation":{"cited_paper":{"arxiv_id":"2307.00495","last_updated":"2024-06-18T14:11:01Z","snapshot_observed_at":"2026-08-09T01:24:56.873715Z","submitted_at":"2023-07-02T06:56:52Z","title":"STG4Traffic: A Survey and Benchmark of Spatial-Temporal Graph Neural Networks for Traffic Prediction","version":2},"cited_work":{"arxiv_id":"2307.00495","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2307.00495","snapshot_observed_at":"2026-07-03T01:17:30.943406Z","title":"Stg4traffic: A survey and bench- mark of spatial-temporal graph neural networks for traffic prediction,","venue":null,"work_id":"e08916f2-b151-4f8b-a399-b37f12930f56","year":2023},"citing_paper":{"arxiv_id":"2606.09539","last_updated":"2026-06-08T14:23:56Z","snapshot_observed_at":"2026-08-06T12:49:34.266904Z","submitted_at":"2026-06-08T14:23:56Z","title":"Efficient Traffic Prediction at Scale: A Systematic Study of STGCN Architectural Depth","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-06-27T17:32:48.804832Z"},"links":{"cited_paper":"/paper/2307.00495","citing_paper":"/paper/2606.09539"},"observation_digest":"sha256:b44ea1a7cb3907ba512a75d51f03eedac95e6a53d1ab726845fa6640cabe4b01","observation_id":"b771021b-4af3-4b62-a5ea-7dff5c498a66","resolution":{"observed_at":"2026-07-03T00:07:27.722776Z","resolver_source":"arxiv_id","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/2307.00495/citation-record","integrity":"/paper/2307.00495/integrity","json":"/paper/2307.00495/citation-record.json","paper":"/paper/2307.00495"},"outbound":[],"paper":{"arxiv_id":"2307.00495","last_updated":"2024-06-18T14:11:01Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-09T01:24:56.873715Z","submitted_at":"2023-07-02T06:56:52Z","title":"STG4Traffic: A Survey and Benchmark of Spatial-Temporal Graph Neural Networks for Traffic Prediction"},"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 3 inbound Pith citation observations for arXiv:2307.00495."}