{"as_of":"2026-08-10T14:59:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:020c164aca29ea673c5f3548c650c3ab64097b3aa405fc59b25dd26f25f37f10","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":"2026-08-10T06:31:04.303077+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":"2026-08-06T22:51:08.065956Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":14,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2101.02118","last_updated":"2021-10-20T10:44:22Z","snapshot_observed_at":"2026-08-09T16:13:57.084206Z","submitted_at":"2021-01-06T16:18:04Z","title":"Do We Really Need Deep Learning Models for Time Series Forecasting?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2101.02118","snapshot_observed_at":"2026-08-06T22:51:08.065956Z","title":"Do we really need deep learning models for time series forecasting? URL http: //arxiv.org/abs/2101.02118","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20574","last_updated":"2025-06-25T16:08:22Z","snapshot_observed_at":"2026-08-10T06:42:54.784760Z","submitted_at":"2025-06-25T16:08:22Z","title":"Benchmarking Unsupervised Strategies for Anomaly Detection in Multivariate Time Series","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-06T22:51:08.065956Z"},"links":{"cited_paper":"/paper/2101.02118","citing_paper":"/paper/2506.20574"},"observation_digest":"sha256:e03cfafca91694817440c8850991b8d2833d9e2d1e1e17865e66e31e30ef0b2d","observation_id":"0ef6f986-3141-4493-971f-0bdb23b16c7c","resolution":{"observed_at":"2026-08-06T22:51:08.065956Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2101.02118","last_updated":"2021-10-20T10:44:22Z","snapshot_observed_at":"2026-08-09T16:13:57.084206Z","submitted_at":"2021-01-06T16:18:04Z","title":"Do We Really Need Deep Learning Models for Time Series Forecasting?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2101.02118","snapshot_observed_at":"2026-08-05T23:26:12.689566Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.05416","last_updated":"2025-08-07T14:08:45Z","snapshot_observed_at":"2026-08-09T15:25:50.374461Z","submitted_at":"2025-08-07T14:08:45Z","title":"Echo State Networks for Bitcoin Time Series Prediction","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-05T23:26:12.689566Z"},"links":{"cited_paper":"/paper/2101.02118","citing_paper":"/paper/2508.05416"},"observation_digest":"sha256:3b363d60df83ca706f6d69c0e4c20210643e20a015f3c5957fa778bf93eb39a8","observation_id":"644a4832-c498-4957-b537-27d404943e09","resolution":{"observed_at":"2026-08-05T23:26:12.689566Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2101.02118","last_updated":"2021-10-20T10:44:22Z","snapshot_observed_at":"2026-08-09T16:13:57.084206Z","submitted_at":"2021-01-06T16:18:04Z","title":"Do We Really Need Deep Learning Models for Time Series Forecasting?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2101.02118","snapshot_observed_at":"2026-08-05T15:10:28.327471Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.20437","last_updated":"2025-08-28T05:27:45Z","snapshot_observed_at":"2026-08-08T13:59:36.660861Z","submitted_at":"2025-08-28T05:27:45Z","title":"On Identifying Why and When Foundation Models Perform Well on Time-Series Forecasting Using Automated Explanations and Rating","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-05T15:10:28.327471Z"},"links":{"cited_paper":"/paper/2101.02118","citing_paper":"/paper/2508.20437"},"observation_digest":"sha256:fa35f0b737381685f84fc44c2117135db84ac0e71b473372c76c2b9269d2c0ec","observation_id":"efdb51d6-5c84-42fd-a638-fed69642fe3d","resolution":{"observed_at":"2026-08-05T15:10:28.327471Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2101.02118","last_updated":"2021-10-20T10:44:22Z","snapshot_observed_at":"2026-08-09T16:13:57.084206Z","submitted_at":"2021-01-06T16:18:04Z","title":"Do We Really Need Deep Learning Models for Time Series Forecasting?","version":2},"cited_work":{"arxiv_id":"2101.02118","doi":"10.48550/arxiv.2101.02118","metadata_source":"arxiv_reference","pith_arxiv_id":"2101.02118","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"arXiv (Cornell University)","work_id":"bad9c770-593e-4baf-8fe1-ec81bf636644","year":null},"citing_paper":{"arxiv_id":"2605.05493","last_updated":"2026-05-06T22:27:50Z","snapshot_observed_at":"2026-08-03T00:00:48.387252Z","submitted_at":"2026-05-06T22:27:50Z","title":"A renormalization-group inspired lattice-based framework for piecewise generalized linear models","version":1},"reference_index":179,"source":"arxiv_source","source_observed_at":"2026-05-08T15:49:33.695290Z"},"links":{"cited_paper":"/paper/2101.02118","citing_paper":"/paper/2605.05493"},"observation_digest":"sha256:17051af124b4075ff3689a45f2413e978afc739e46d810c81dcb8a22fd7516e9","observation_id":"7e5826fc-affd-4a5f-ae99-03847831450b","resolution":{"observed_at":"2026-05-08T20:59:12.242156Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2101.02118/citation-record","integrity":"/paper/2101.02118/integrity","json":"/paper/2101.02118/citation-record.json","paper":"/paper/2101.02118"},"outbound":[],"paper":{"arxiv_id":"2101.02118","last_updated":"2021-10-20T10:44:22Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-09T16:13:57.084206Z","submitted_at":"2021-01-06T16:18:04Z","title":"Do We Really Need Deep Learning Models 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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2101.02118."}