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Paper Citation Record · LEDGER

Enhancing Foundation Models for Time Series Forecasting via Wavelet-based Tokenization

As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2412.05244.

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

pith.paper-citation-record.v1
2412.05244 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-14T15:32:53.282167Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T01:16:24.872523Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 5267a702-fa7c-400e-b976-ee51c5c81c15 · inbound

What If We Let Forecasting Forget? A Sparse Bottleneck for Cross-Variable Dependencies cites this paper.

What If We Let Forecasting Forget? A Sparse Bottleneck for Cross-Variable Dependencies Enhancing Foundation Models for Time Series Forecasting via Wavelet-based Tokenization

Reference 66

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T07:31:26.940264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-05-12T02:36:18.686443Z digest=sha256:797b10a8acc1897d20b31355346a4a2fbebd090c0df3ebaad6f9ef03cee1d619

Observation 9b2043d4-cc36-40d8-b012-f7e1a6c46d87 · inbound

Spectral Vision Transformer for Efficient Tokenization with Limited Data cites this paper.

Spectral Vision Transformer for Efficient Tokenization with Limited Data Enhancing Foundation Models for Time Series Forecasting via Wavelet-based Tokenization

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-05-13T06:57:28.171802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-13T06:53:51.211617Z digest=sha256:3f04ee843597ba8514c4fc2371932efb47c899f22ebecb53daa4160ad486c32d

Observation 51a3e9e1-c534-4b5b-8ca0-0691b5d6975c · inbound

Data-Driven Forecasting of three-Component Seismograms Using Transformer Architectures cites this paper.

Data-Driven Forecasting of three-Component Seismograms Using Transformer Architectures Enhancing Foundation Models for Time Series Forecasting via Wavelet-based Tokenization

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-07-02T01:16:24.874506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-28T12:15:29.291378Z digest=sha256:1aa14976baa5c39e9a023522307e93b465cbca3ab1d50fd8f7f964ca2a7d9767

Observation f71556e7-3ca9-4774-b036-d1733334541d · inbound

Data-Driven Forecasting of three-Component Seismograms Using Transformer Architectures cites this paper.

Data-Driven Forecasting of three-Component Seismograms Using Transformer Architectures Enhancing Foundation Models for Time Series Forecasting via Wavelet-based Tokenization

Reference 36

Resolution
unresolved
no resolver link, observed 2026-07-12T15:18:09.444513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T15:18:09.444513Z digest=sha256:c5c3153eddd0cae7b84e60309d725a903a6d153ac673c89074329a1a73db685d

Observation 1c3eab99-d0e2-47f9-a5e6-04eae20799dd · inbound

JEPA for AI-Native 6G: Predictive Representations and Open Challenges cites this paper.

JEPA for AI-Native 6G: Predictive Representations and Open Challenges Enhancing Foundation Models for Time Series Forecasting via Wavelet-based Tokenization

Reference 14

Resolution
unresolved
no resolver link, observed 2026-07-14T15:32:53.282167Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T15:32:53.282167Z digest=sha256:e0f4302625551d7df27ac01ea85f06e49c3c07ea778c417704ba6caa9cb17479