Paper Citation Record · LEDGER

Position: Current Benchmarking Hinders Real Progress in Deep Learning for Time Series Forecasting

As of 8 August 2026, this Paper Citation Record lists 9 of 9 outbound references and 0 inbound Pith citation observations for arXiv:2512.22702.

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

pith.paper-citation-record.v1
2512.22702 v2

Coverage vector

measured 9 of 9 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T13:51:03.460397Z

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

9 of 9 outbound references displayed

verified exact0
verified fuzzy0
unresolved8
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2f22f585-9f6e-4625-8ddc-2c3e76ebdb29 · outbound

This paper cites An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling.

Position: Current Benchmarking Hinders Real Progress in Deep Learning for Time Series Forecasting An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T13:51:02.812570Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5aa1b372-76f7-4778-923f-98fe64f4be3a · outbound

This paper cites Long-Range Transformers for Dynamic Spatiotemporal Forecasting.

Position: Current Benchmarking Hinders Real Progress in Deep Learning for Time Series Forecasting Long-Range Transformers for Dynamic Spatiotemporal Forecasting

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-03T13:51:03.122673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d8b8434-95a5-4f48-8a6f-c065d249cdcd · outbound

This paper cites Furthermore, we summarize them in Tab.

Position: Current Benchmarking Hinders Real Progress in Deep Learning for Time Series Forecasting Furthermore, we summarize them in Tab

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T13:51:03.343354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74cd9fd1-9a85-492d-8516-4b22efa54404 · outbound

This paper cites an unresolved cited work.

Position: Current Benchmarking Hinders Real Progress in Deep Learning for Time Series Forecasting Unresolved cited work

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T13:51:03.401450Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14d1b1e1-9156-4e85-ba0c-aa371f0cc0f2 · outbound

This paper cites an unresolved cited work.

Position: Current Benchmarking Hinders Real Progress in Deep Learning for Time Series Forecasting Unresolved cited work

Reference 32

Resolution: malformed identifier; no resolver link, observed 2026-08-03T13:51:03.460397Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84195aa3-6bd4-42c0-8250-b74fdeef03e3 · outbound

This paper cites iTransformer: Inverted Transformers Are Effective for Time Series Forecasting.

Position: Current Benchmarking Hinders Real Progress in Deep Learning for Time Series Forecasting iTransformer: Inverted Transformers Are Effective for Time Series Forecasting

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-03T13:51:03.183910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68359f3e-bfa1-46a6-a3cf-dd4d99f5e4bb · outbound

This paper cites an unresolved cited work.

Position: Current Benchmarking Hinders Real Progress in Deep Learning for Time Series Forecasting Unresolved cited work

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-03T13:51:03.222279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b18ecc09-63b5-4a11-ad26-a5fd623b0424 · outbound

This paper cites doi: 10.1145/3533382.

Position: Current Benchmarking Hinders Real Progress in Deep Learning for Time Series Forecasting doi: 10.1145/3533382

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-03T13:51:02.883804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3edeca64-4b71-4da6-8c2b-74602ff4e94b · outbound

This paper cites an unresolved cited work.

Position: Current Benchmarking Hinders Real Progress in Deep Learning for Time Series Forecasting Unresolved cited work

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-03T13:51:02.975604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.