Paper Citation Record · LEDGER

Evaluating Time Series Foundation Models on Noisy Periodic Time Series

As of 20 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2501.00889.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2501.00889 v2

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:43:53.262283Z

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

15 of 15 outbound references displayed

verified exact0
verified fuzzy4
unresolved11
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9af53ac8-4828-4d3a-a538-56ce8d08ad02 · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

Evaluating Time Series Foundation Models on Noisy Periodic Time Series On the Opportunities and Risks of Foundation Models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T22:43:53.209236Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf12f2cd-af17-4580-97a9-d57a840d89dc · outbound

This paper cites Language models are few-shot learners,.

Evaluating Time Series Foundation Models on Noisy Periodic Time Series Language models are few-shot learners,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:43:53.537963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e22fa44d-e8f9-4537-8300-07c8c0f0319b · outbound

This paper cites Foundation models for time series analysis: A tutorial and survey,.

Evaluating Time Series Foundation Models on Noisy Periodic Time Series Foundation models for time series analysis: A tutorial and survey,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:43:53.526860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f4d45d08-be88-4480-90be-5576677d97b1 · outbound

This paper cites A survey of time series foundation models: Generalizing time series representation with large language mode,.

Evaluating Time Series Foundation Models on Noisy Periodic Time Series A survey of time series foundation models: Generalizing time series representation with large language mode,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T22:43:53.222033Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c1b0f33c-6300-4fbc-8cf0-03ee04e62a03 · outbound

This paper cites A Survey of Deep Learning and Foundation Models for Time Series Forecasting.

Evaluating Time Series Foundation Models on Noisy Periodic Time Series A Survey of Deep Learning and Foundation Models for Time Series Forecasting

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T22:43:53.226090Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf4795d3-0fbf-4ccf-bfab-669a4cc6fda4 · outbound

This paper cites Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting.

Evaluating Time Series Foundation Models on Noisy Periodic Time Series Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-10T22:43:53.230271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e160519a-ddf0-4a3f-9e27-cbce0523cc4f · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Evaluating Time Series Foundation Models on Noisy Periodic Time Series Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T22:43:53.234661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b43ab8e7-746c-4d1e-955e-85dcb0274f59 · outbound

This paper cites Chronos: Learning the Language of Time Series.

Evaluating Time Series Foundation Models on Noisy Periodic Time Series Chronos: Learning the Language of Time Series

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T22:43:53.238876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36375b34-4a8a-4e49-b5cc-0d2397c08527 · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer,.

Evaluating Time Series Foundation Models on Noisy Periodic Time Series Exploring the limits of transfer learning with a unified text-to-text transformer,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T22:43:53.242481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eeee0c1f-fb01-45ab-9d7c-c4e37bb23992 · outbound

This paper cites Unified Training of Universal Time Series Forecasting Transformers.

Evaluating Time Series Foundation Models on Noisy Periodic Time Series Unified Training of Universal Time Series Forecasting Transformers

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T22:43:53.245729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 554c8284-1ceb-41a7-8539-ff2ef7954ba9 · outbound

This paper cites A decoder-only foundation model for time-series forecasting.

Evaluating Time Series Foundation Models on Noisy Periodic Time Series A decoder-only foundation model for time-series forecasting

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T22:43:53.249253Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49c18260-1928-4743-982c-0793fb1cc08c · outbound

This paper cites On the processing of harmonics and interharmonics: Using hanning window in standard framework,.

Evaluating Time Series Foundation Models on Noisy Periodic Time Series On the processing of harmonics and interharmonics: Using hanning window in standard framework,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:43:53.509525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b55c2bab-6b6b-4681-bbdc-dfe64efa74c6 · outbound

This paper cites an unresolved cited work.

Evaluating Time Series Foundation Models on Noisy Periodic Time Series Unresolved cited work

Reference 13

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:43:53.498282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 25905970-8c28-4971-84fe-76bec0823ded · outbound

This paper cites An algorithm for the machine calculation of complex fourier series,.

Evaluating Time Series Foundation Models on Noisy Periodic Time Series An algorithm for the machine calculation of complex fourier series,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-10T22:43:53.259167Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17150c3c-0063-40b7-9d60-2e0d6d90e186 · outbound

This paper cites Information theory and an extension of the maximum likelihood principle,.

Evaluating Time Series Foundation Models on Noisy Periodic Time Series Information theory and an extension of the maximum likelihood principle,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:43:53.479636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

No inbound Pith citation observations are available.