{"as_of":"2026-08-15T09:38:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d5699c72f5ccd336532bf5c81bec59d58f776db8a9d0ab3d6c96a6bac09178cd","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":4,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":4,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T10:56:09.320572Z","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":"2026-07-03T04:07:37.184589Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2306.05035","last_updated":"2024-02-04T04:42:26Z","snapshot_observed_at":"2026-08-13T11:21:59.377456Z","submitted_at":"2023-06-08T08:37:49Z","title":"Does Long-Term Series Forecasting Need Complex Attention and Extra Long Inputs?","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.05035","snapshot_observed_at":"2026-08-12T10:56:09.320572Z","title":"Does long- term series forecasting need complex attention and extra long inputs?","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.00108","last_updated":"2024-11-28T01:39:45Z","snapshot_observed_at":"2026-08-13T03:19:05.798733Z","submitted_at":"2024-11-28T01:39:45Z","title":"Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-12T10:56:09.320572Z"},"links":{"cited_paper":"/paper/2306.05035","citing_paper":"/paper/2412.00108"},"observation_digest":"sha256:304ddfb5ee511dd03a0f514f8983200ce0e302bec85d68d6e99c19c26e64854b","observation_id":"7997fcf4-dee6-4873-bc37-502e8a7698f3","resolution":{"observed_at":"2026-08-12T10:56:09.320572Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.05035","last_updated":"2024-02-04T04:42:26Z","snapshot_observed_at":"2026-08-13T11:21:59.377456Z","submitted_at":"2023-06-08T08:37:49Z","title":"Does Long-Term Series Forecasting Need Complex Attention and Extra Long Inputs?","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.05035","snapshot_observed_at":"2026-08-10T21:25:42.239205Z","title":"Does long- term series forecasting need complex attention and extra long inputs?","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.06255","last_updated":"2025-01-09T03:35:00Z","snapshot_observed_at":"2026-08-15T05:25:23.636998Z","submitted_at":"2025-01-09T03:35:00Z","title":"Progressive Supervision via Label Decomposition: An Long-Term and Large-Scale Wireless Traffic Forecasting Method","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-10T21:25:42.239205Z"},"links":{"cited_paper":"/paper/2306.05035","citing_paper":"/paper/2501.06255"},"observation_digest":"sha256:7d9e82dd075ee032c87bd4611a5fd8bc35985e211c1dbe3720c3dd1e20ec64c7","observation_id":"91a7c77f-7be1-46c4-9ec4-8b13887d4693","resolution":{"observed_at":"2026-08-10T21:25:42.239205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.05035","last_updated":"2024-02-04T04:42:26Z","snapshot_observed_at":"2026-08-13T11:21:59.377456Z","submitted_at":"2023-06-08T08:37:49Z","title":"Does Long-Term Series Forecasting Need Complex Attention and Extra Long Inputs?","version":3},"cited_work":{"arxiv_id":"2306.05035","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2306.05035","snapshot_observed_at":"2026-07-03T04:07:37.184589Z","title":"arXiv preprint arXiv:2306.05035 , year=","venue":null,"work_id":"6959216e-ed18-4291-93fc-1f38cadeb446","year":null},"citing_paper":{"arxiv_id":"2606.10592","last_updated":"2026-06-09T08:56:21Z","snapshot_observed_at":"2026-08-14T11:12:07.560449Z","submitted_at":"2026-06-09T08:56:21Z","title":"Dirichlet-Guided Group Forecasting for Alleviating Over-smoothing in Time Series Forecasting","version":1},"reference_index":73,"source":"arxiv_source","source_observed_at":"2026-06-27T14:07:11.942435Z"},"links":{"cited_paper":"/paper/2306.05035","citing_paper":"/paper/2606.10592"},"observation_digest":"sha256:5197a30afe77a6fb42191644cb4a8ecf08ea27ad3486481a64aaa79206c6420a","observation_id":"5a2e7dfe-aa8e-4e5b-b259-b013b65c8890","resolution":{"observed_at":"2026-07-03T04:07:37.186286Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.05035","last_updated":"2024-02-04T04:42:26Z","snapshot_observed_at":"2026-08-13T11:21:59.377456Z","submitted_at":"2023-06-08T08:37:49Z","title":"Does Long-Term Series Forecasting Need Complex Attention and Extra Long Inputs?","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.05035","snapshot_observed_at":"2026-08-12T00:39:40.668429Z","title":"arXiv preprint arXiv:2306.05035 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.08010","last_updated":"2026-08-08T08:41:33Z","snapshot_observed_at":"2026-08-14T23:53:56.884408Z","submitted_at":"2026-08-08T08:41:33Z","title":"Ground-Truth Neighborhood Regularization for Reinforcement Learning Post-Training of Time Series Foundation Models","version":1},"reference_index":86,"source":"arxiv_source","source_observed_at":"2026-08-12T00:39:40.668429Z"},"links":{"cited_paper":"/paper/2306.05035","citing_paper":"/paper/2608.08010"},"observation_digest":"sha256:0b2ae097ebe5a7c8ad98b31d71173832844be31796ca8d85e46d6b2f0f5e272b","observation_id":"20ca69bf-ae28-4340-b566-c821ff986390","resolution":{"observed_at":"2026-08-12T00:39:40.668429Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2306.05035/citation-record","integrity":"/paper/2306.05035/integrity","json":"/paper/2306.05035/citation-record.json","paper":"/paper/2306.05035"},"outbound":[],"paper":{"arxiv_id":"2306.05035","last_updated":"2024-02-04T04:42:26Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-13T11:21:59.377456Z","submitted_at":"2023-06-08T08:37:49Z","title":"Does Long-Term Series Forecasting Need Complex Attention and Extra Long Inputs?"},"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":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2306.05035."}