{"as_of":"2026-08-10T11:20:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:150dc643930995c93069728d5b228ff927dbe5271075f65d51af86261227b4fb","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":"2026-08-10T06:31:04.303077+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":"2026-08-08T00:50:44.708565Z","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":"2026-08-06T21:07:12.876026Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2203.07681","last_updated":"2022-03-15T06:51:58Z","snapshot_observed_at":"2026-08-10T11:03:22.250895Z","submitted_at":"2022-03-15T06:51:58Z","title":"DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.07681","snapshot_observed_at":"2026-08-07T04:53:32.948278Z","title":"Depts: deep expansion learning for periodic time series forecasting","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.09526","last_updated":"2025-06-11T08:52:01Z","snapshot_observed_at":"2026-08-08T23:15:25.699531Z","submitted_at":"2025-06-11T08:52:01Z","title":"Neural Functions for Learning Periodic Signal","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T04:53:32.948278Z"},"links":{"cited_paper":"/paper/2203.07681","citing_paper":"/paper/2506.09526"},"observation_digest":"sha256:09e7aad06e31ae7028c9d93e0b214f53016f897a5b884dc45ad441667a60c00b","observation_id":"ff4e317e-5396-49d8-b325-ad52ff6a793e","resolution":{"observed_at":"2026-08-07T04:53:32.948278Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.07681","last_updated":"2022-03-15T06:51:58Z","snapshot_observed_at":"2026-08-10T11:03:22.250895Z","submitted_at":"2022-03-15T06:51:58Z","title":"DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting","version":1},"cited_work":{"arxiv_id":"2203.07681","doi":null,"metadata_source":"pith","pith_arxiv_id":"2203.07681","snapshot_observed_at":"2026-08-06T21:07:12.876026Z","title":"DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting","venue":"cs.LG","work_id":"e77694e2-a47c-4655-a39c-c4f0b80ff191","year":2022},"citing_paper":{"arxiv_id":"2507.00914","last_updated":"2025-07-01T16:18:29Z","snapshot_observed_at":"2026-08-08T07:46:11.219377Z","submitted_at":"2025-07-01T16:18:29Z","title":"Large Language Model Powered Intelligent Urban Agents: Concepts, Capabilities, and Applications","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T21:07:05.834302Z"},"links":{"cited_paper":"/paper/2203.07681","citing_paper":"/paper/2507.00914"},"observation_digest":"sha256:1a95a166273e3bbe4a072a27b33da0583b3958d6aa687ebfc7abd032c0610ebe","observation_id":"f15d2809-b955-4430-94ae-b4eccbdfa013","resolution":{"observed_at":"2026-08-06T21:07:12.879987Z","resolver_source":"local_arxiv","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"}},{"citation":{"cited_paper":{"arxiv_id":"2203.07681","last_updated":"2022-03-15T06:51:58Z","snapshot_observed_at":"2026-08-10T11:03:22.250895Z","submitted_at":"2022-03-15T06:51:58Z","title":"DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.07681","snapshot_observed_at":"2026-08-08T00:50:44.708565Z","title":"arXiv preprint arXiv:2203.07681 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04051","last_updated":"2026-08-04T10:04:16Z","snapshot_observed_at":"2026-08-08T23:10:55.386268Z","submitted_at":"2026-08-04T10:04:16Z","title":"CAMP: A Cycle-Aware Multi-Scale Patch Mixer for Time Series Forecasting","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-08T00:50:44.708565Z"},"links":{"cited_paper":"/paper/2203.07681","citing_paper":"/paper/2608.04051"},"observation_digest":"sha256:79278e497c40fb43963187025ee5457d91c52ef6b88e124debe20eb64837c085","observation_id":"9e5b804b-8bbd-4d41-861b-6b59b8b04ae4","resolution":{"observed_at":"2026-08-08T00:50:44.708565Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2203.07681/citation-record","integrity":"/paper/2203.07681/integrity","json":"/paper/2203.07681/citation-record.json","paper":"/paper/2203.07681"},"outbound":[],"paper":{"arxiv_id":"2203.07681","last_updated":"2022-03-15T06:51:58Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-10T11:03:22.250895Z","submitted_at":"2022-03-15T06:51:58Z","title":"DEPTS: Deep Expansion Learning for Periodic 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 3 inbound Pith citation observations for arXiv:2203.07681."}