Paper Citation Record · LEDGER

Do We Really Need Deep Learning Models for Time Series Forecasting?

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.

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

pith.paper-citation-record.v1
2101.02118 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:51:08.065956Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

14
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 0ef6f986-3141-4493-971f-0bdb23b16c7c · inbound

Benchmarking Unsupervised Strategies for Anomaly Detection in Multivariate Time Series cites this paper.

Benchmarking Unsupervised Strategies for Anomaly Detection in Multivariate Time Series Do We Really Need Deep Learning Models for Time Series Forecasting?

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-06T22:51:08.065956Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 644a4832-c498-4957-b537-27d404943e09 · inbound

Echo State Networks for Bitcoin Time Series Prediction cites this paper.

Echo State Networks for Bitcoin Time Series Prediction Do We Really Need Deep Learning Models for Time Series Forecasting?

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-05T23:26:12.689566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation efdb51d6-5c84-42fd-a638-fed69642fe3d · inbound

On Identifying Why and When Foundation Models Perform Well on Time-Series Forecasting Using Automated Explanations and Rating cites this paper.

On Identifying Why and When Foundation Models Perform Well on Time-Series Forecasting Using Automated Explanations and Rating Do We Really Need Deep Learning Models for Time Series Forecasting?

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-05T15:10:28.327471Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e5826fc-affd-4a5f-ae99-03847831450b · inbound

A renormalization-group inspired lattice-based framework for piecewise generalized linear models cites this paper.

A renormalization-group inspired lattice-based framework for piecewise generalized linear models Do We Really Need Deep Learning Models for Time Series Forecasting?

Reference 179

Resolution: verified exact; arxiv_id, observed 2026-05-08T20:59:12.242156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.