Pith. sign in

Paper Citation Record · LEDGER

Employing Discrete Fourier Transform in Representational Learning

As of 8 August 2026, this Paper Citation Record lists 8 of 8 outbound references and 0 inbound Pith citation observations for arXiv:2506.06765.

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

pith.paper-citation-record.v1
2506.06765 v1

Coverage vector

measured 8 of 8 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:55:36.401322Z

measured 8 of 8 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

8 of 8 outbound references displayed

  • verified exact0
  • verified fuzzy6
  • unresolved2
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 16785138-e09a-481a-a4be-fb67c9ad3259 · outbound

This paper cites Representation Learning: A Review and New Perspectives.

Employing Discrete Fourier Transform in Representational Learning Representation Learning: A Review and New Perspectives

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:55:36.519618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T05:55:36.371666Z digest=sha256:ba6a2772baf0bf8072cdf4a5b3966bd51b12a06c16af07fc33cdf5d5d0441f7d

Observation cec42c8e-d439-4c0f-9d02-a081bfd9b2fc · outbound

This paper cites To Compress or Not to Compress- Self-Supervised Learning and Information Theory: A Review.

Employing Discrete Fourier Transform in Representational Learning To Compress or Not to Compress- Self-Supervised Learning and Information Theory: A Review

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-07T05:55:36.376105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:55:36.376105Z digest=sha256:b7bec068cbcd2b95a0f91eec711b0bf3e9d07955864d0a4c17a54dd2fa4ad192

Observation c028d7e5-b89b-4bb1-bc60-d72cb91fee15 · outbound

This paper cites Transforming Auto-Encoders.

Employing Discrete Fourier Transform in Representational Learning Transforming Auto-Encoders

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:55:36.507657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T05:55:36.380558Z digest=sha256:183fbe0c2e64458d253df078eb604a1b884f2adf6991337d8ddc647d0863cb81

Observation ebe005ea-0400-49a7-8bb2-074c72b48430 · outbound

This paper cites Torralba and A.

Employing Discrete Fourier Transform in Representational Learning Torralba and A

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:55:36.496930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T05:55:36.384528Z digest=sha256:aee38579fc667e7751637dbe2adb0f4eac42b15312fe741392a3b48a81f30128

Observation c4fe0876-03bd-4aae-b452-dfd175f5108c · outbound

This paper cites VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning.

Employing Discrete Fourier Transform in Representational Learning VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T05:55:36.388663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:55:36.388663Z digest=sha256:fd5a40205a842430f6c1297454706ce24d9bf5a08e49891dd81c01190fca7b29

Observation c6e853cc-d587-482a-89e8-5386182c316c · outbound

This paper cites Deep Residual Learning for Image Recognition.

Employing Discrete Fourier Transform in Representational Learning Deep Residual Learning for Image Recognition

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:55:36.484571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T05:55:36.393139Z digest=sha256:50ecd0969f0773fe97578aa2771acb1b11bac75f4cbd4e76c057af8198b20b24

Observation d8631ad1-bf75-46ee-a00d-0214b96b818f · outbound

This paper cites Learning Multiple Layers of Features from Tiny Images.

Employing Discrete Fourier Transform in Representational Learning Learning Multiple Layers of Features from Tiny Images

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:55:36.473222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T05:55:36.397706Z digest=sha256:1a7ed18ada2ce6ae9d17841c1d274d1a0a1df29aaca0016fc4c32749e039192c

Observation aa86fb6e-3a53-45a9-90a1-d4bbf726f842 · outbound

This paper cites ImageNet: A large-scale hierarchical image database.

Employing Discrete Fourier Transform in Representational Learning ImageNet: A large-scale hierarchical image database

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:55:36.460459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T05:55:36.401322Z digest=sha256:c4b7d92cef5ef1544b4367d4b5b3d3a63deccfc0275d2c5b97e273135fd233e8

Pith citing papers

No inbound Pith citation observations are available.