{"as_of":"2026-08-08T08:32:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:35598df47c4a39f9fd927d7daaa46e356d44ff1e3e5447a05f86d63c491fa05c","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":"2026-08-08T06:32:00.761636+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":"2026-08-07T14:16:21.533167Z","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":"2026-05-24T04:28:53.434192Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2405.10597","last_updated":"2024-05-17T07:47:11Z","snapshot_observed_at":"2026-07-06T18:15:37.711235Z","submitted_at":"2024-05-17T07:47:11Z","title":"UniCL: A Universal Contrastive Learning Framework for Large Time Series Models","version":1},"cited_work":{"arxiv_id":"2405.10597","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2405.10597","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"296dc199-da5b-4246-b751-25df32c11440","year":2024},"citing_paper":{"arxiv_id":"2401.03717","last_updated":"2026-05-16T18:59:42Z","snapshot_observed_at":"2026-08-02T21:39:50.574099Z","submitted_at":"2024-01-08T08:00:04Z","title":"Universal Time-Series Representation Learning: A Survey","version":4},"reference_index":113,"source":"pdf_text","source_observed_at":"2026-05-24T04:26:45.527625Z"},"links":{"cited_paper":"/paper/2405.10597","citing_paper":"/paper/2401.03717"},"observation_digest":"sha256:f125cf2abe9a162de21d1eaba071d0fbfebf59d1d357cd7978f91f439ac064ad","observation_id":"c7396559-9650-471f-8f66-02a1f346c736","resolution":{"observed_at":"2026-05-24T04:28:53.436768Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.10597","last_updated":"2024-05-17T07:47:11Z","snapshot_observed_at":"2026-07-06T18:15:37.711235Z","submitted_at":"2024-05-17T07:47:11Z","title":"UniCL: A Universal Contrastive Learning Framework for Large Time Series Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.10597","snapshot_observed_at":"2026-08-07T14:16:21.533167Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.19620","last_updated":"2025-05-26T07:37:39Z","snapshot_observed_at":"2026-08-07T14:07:53.903851Z","submitted_at":"2025-05-26T07:37:39Z","title":"Decoupling Spatio-Temporal Prediction: When Lightweight Large Models Meet Adaptive Hypergraphs","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T14:16:21.533167Z"},"links":{"cited_paper":"/paper/2405.10597","citing_paper":"/paper/2505.19620"},"observation_digest":"sha256:89d697f70ae5f59941f82607fe8c6d6fffc7ded3024b8592bb683bd8a7c55d3d","observation_id":"847f3e85-3439-4821-853a-e1734036a08e","resolution":{"observed_at":"2026-08-07T14:16:21.533167Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2405.10597/citation-record","integrity":"/paper/2405.10597/integrity","json":"/paper/2405.10597/citation-record.json","paper":"/paper/2405.10597"},"outbound":[],"paper":{"arxiv_id":"2405.10597","last_updated":"2024-05-17T07:47:11Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T18:15:37.711235Z","submitted_at":"2024-05-17T07:47:11Z","title":"UniCL: A Universal Contrastive Learning Framework for Large Time Series Models"},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2405.10597."}