{"as_of":"2026-08-13T11:53:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8acb10e8708507ac64160a0fd33c27d798a145ee8e3cdb79a5bf67bf53914ad9","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":"2026-08-13T06:32:02.005865+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":"2026-08-12T20:56:16.973263Z","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":"2026-08-12T18:37:07.392158Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2405.03255","last_updated":"2024-05-06T08:24:06Z","snapshot_observed_at":"2026-08-13T00:14:12.525901Z","submitted_at":"2024-05-06T08:24:06Z","title":"Multi-Modality Spatio-Temporal Forecasting via Self-Supervised Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.03255","snapshot_observed_at":"2026-08-12T20:56:16.973263Z","title":"Multi-modality spatio- temporal forecasting via self-supervised learning,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.09251","last_updated":"2024-11-14T07:34:31Z","snapshot_observed_at":"2026-08-13T04:08:29.444752Z","submitted_at":"2024-11-14T07:34:31Z","title":"Cross Space and Time: A Spatio-Temporal Unitized Model for Traffic Flow Forecasting","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-12T20:56:16.973263Z"},"links":{"cited_paper":"/paper/2405.03255","citing_paper":"/paper/2411.09251"},"observation_digest":"sha256:f7a3db741700e21a191a8628212250f0a5ed8af8126412ec0674542ed69a2555","observation_id":"a9731b97-8048-41c6-99fe-7e3b0182f82e","resolution":{"observed_at":"2026-08-12T20:56:16.973263Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.03255","last_updated":"2024-05-06T08:24:06Z","snapshot_observed_at":"2026-08-13T00:14:12.525901Z","submitted_at":"2024-05-06T08:24:06Z","title":"Multi-Modality Spatio-Temporal Forecasting via Self-Supervised Learning","version":1},"cited_work":{"arxiv_id":"2405.03255","doi":null,"metadata_source":"pith","pith_arxiv_id":"2405.03255","snapshot_observed_at":"2026-08-12T18:37:07.392158Z","title":"Multi-Modality Spatio-Temporal Forecasting via Self-Supervised Learning","venue":"cs.LG","work_id":"1e2558b4-7b0a-4423-9901-340d4b5a7304","year":2024},"citing_paper":{"arxiv_id":"2411.11448","last_updated":"2024-11-18T10:30:34Z","snapshot_observed_at":"2026-08-12T18:28:25.943500Z","submitted_at":"2024-11-18T10:30:34Z","title":"Unveiling the Inflexibility of Adaptive Embedding in Traffic Forecasting","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-12T18:37:07.174738Z"},"links":{"cited_paper":"/paper/2405.03255","citing_paper":"/paper/2411.11448"},"observation_digest":"sha256:8ba0420b4d726dfc849668a2a5732ccc3b873acf989e5ee8ef8340fd9d550eca","observation_id":"8169d18e-5392-470f-8b15-c050d0e3dd29","resolution":{"observed_at":"2026-08-12T18:37:07.398763Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2405.03255/citation-record","integrity":"/paper/2405.03255/integrity","json":"/paper/2405.03255/citation-record.json","paper":"/paper/2405.03255"},"outbound":[],"paper":{"arxiv_id":"2405.03255","last_updated":"2024-05-06T08:24:06Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-13T00:14:12.525901Z","submitted_at":"2024-05-06T08:24:06Z","title":"Multi-Modality Spatio-Temporal Forecasting via Self-Supervised Learning"},"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":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2405.03255."}