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Paper Citation Record · LEDGER

Benchmarking the Fairness of Image Upsampling Methods

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2401.13555.

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

pith.paper-citation-record.v1
2401.13555 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:42:53.646756Z

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

0
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 b80095e3-25d8-4ee8-b509-59ce7bcd1ba9 · inbound

Gone With the Bits: Revealing Racial Bias in Low-Rate Neural Compression for Facial Images cites this paper.

Gone With the Bits: Revealing Racial Bias in Low-Rate Neural Compression for Facial Images Benchmarking the Fairness of Image Upsampling Methods

Reference 2012

Resolution
unresolved
no resolver link, observed 2026-08-16T00:42:53.646756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:42:53.646756Z digest=sha256:ce238c3d8cd906794045fd396036dbd18bfd8ae6d3e6f6267fcd43cf50b777a0

Observation a38ec4b0-03b4-49e2-ab2c-eccee09592af · inbound

Unmasking LAION-5B: Age, Gender, Race, and Emotion Biases in Large-Scale Image Datasets cites this paper.

Unmasking LAION-5B: Age, Gender, Race, and Emotion Biases in Large-Scale Image Datasets Benchmarking the Fairness of Image Upsampling Methods

Reference 260

Resolution
verified exact
arxiv_id, observed 2026-06-26T09:19:17.113134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-06-26T09:12:19.873337Z digest=sha256:4ced0fd6f588c2ebc21f09f9f6c68dd6599640adda7a9138eed9ef1002862d66