{"as_of":"2026-08-20T03:57:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:bea84e0a4298f44d7bcdff9e62b11df625f75f9692243ab71005c8e7df99fd22","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":"2026-08-19T06:32:44.657259+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":"2026-08-15T16:44:24.177748Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"pith","source_observed_at":"2026-08-10T05:30:23.456663Z","state":"measured"}],"external_citation_measurements":[{"count":3,"observed_at":"2026-08-10T05:30:23.456663Z","source":"pith"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2305.06587","last_updated":"2025-02-23T01:06:33Z","snapshot_observed_at":"2026-08-16T15:33:58.234675Z","submitted_at":"2023-05-11T05:56:38Z","title":"Towards Expressive Spectral-Temporal Graph Neural Networks for Time Series Forecasting","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.06587","snapshot_observed_at":"2026-08-12T04:45:49.833933Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.01122","last_updated":"2024-12-02T04:58:48Z","snapshot_observed_at":"2026-08-18T20:42:35.696013Z","submitted_at":"2024-12-02T04:58:48Z","title":"TAS-TsC: A Data-Driven Framework for Estimating Time of Arrival Using Temporal-Attribute-Spatial Tri-space Coordination of Truck Trajectories","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-12T04:45:49.833933Z"},"links":{"cited_paper":"/paper/2305.06587","citing_paper":"/paper/2412.01122"},"observation_digest":"sha256:cd69f165a81c651b205bd6226773c01eb5b5b188f5876198d939c8d139945e43","observation_id":"de69395d-b83c-4a22-838a-59c41035c0d5","resolution":{"observed_at":"2026-08-12T04:45:49.833933Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.06587","last_updated":"2025-02-23T01:06:33Z","snapshot_observed_at":"2026-08-16T15:33:58.234675Z","submitted_at":"2023-05-11T05:56:38Z","title":"Towards Expressive Spectral-Temporal Graph Neural Networks for Time Series Forecasting","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.06587","snapshot_observed_at":"2026-08-15T16:44:24.177748Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.21570","last_updated":"2025-08-29T12:25:26Z","snapshot_observed_at":"2026-08-15T16:37:41.260715Z","submitted_at":"2025-08-29T12:25:26Z","title":"OASIS: Harnessing Diffusion Adversarial Network for Ocean Salinity Imputation using Sparse Drifter Trajectories","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-15T16:44:24.177748Z"},"links":{"cited_paper":"/paper/2305.06587","citing_paper":"/paper/2508.21570"},"observation_digest":"sha256:99962b63b778dac02770c8e0de78def0f8944e4cbbe5191f4060a54be8f1fdfb","observation_id":"f43b27a0-32f7-4a6b-b13c-3a79c6b523f9","resolution":{"observed_at":"2026-08-15T16:44:24.177748Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.06587","last_updated":"2025-02-23T01:06:33Z","snapshot_observed_at":"2026-08-16T15:33:58.234675Z","submitted_at":"2023-05-11T05:56:38Z","title":"Towards Expressive Spectral-Temporal Graph Neural Networks for Time Series Forecasting","version":3},"cited_work":{"arxiv_id":"2305.06587","doi":"10.48550/arxiv.2305.06587","metadata_source":"pith","pith_arxiv_id":"2305.06587","snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Towards Expressive Spectral-Temporal Graph Neural Networks for Time Series Forecasting","venue":"cs.LG","work_id":"5737bb13-992a-4578-9c62-8535f723523f","year":2023},"citing_paper":{"arxiv_id":"2509.05768","last_updated":"2025-09-06T16:50:22Z","snapshot_observed_at":"2026-08-13T16:42:51.592792Z","submitted_at":"2025-09-06T16:50:22Z","title":"Real-E: A Foundation Benchmark for Advancing Robust and Generalizable Electricity Forecasting","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-05T05:00:53.501351Z"},"links":{"cited_paper":"/paper/2305.06587","citing_paper":"/paper/2509.05768"},"observation_digest":"sha256:5ab2f1871a92ef7cf562b9cc8b9ff1dca9141fee4c13c2370bde2a6a3fc214c7","observation_id":"6194d66b-4283-4b9c-b8bc-0880a11ef5ef","resolution":{"observed_at":"2026-08-05T05:00:53.630196Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2305.06587/citation-record","integrity":"/paper/2305.06587/integrity","json":"/paper/2305.06587/citation-record.json","paper":"/paper/2305.06587"},"outbound":[],"paper":{"arxiv_id":"2305.06587","last_updated":"2025-02-23T01:06:33Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-16T15:33:58.234675Z","submitted_at":"2023-05-11T05:56:38Z","title":"Towards Expressive Spectral-Temporal Graph Neural Networks for Time Series Forecasting"},"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":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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:2305.06587."}