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Paper Citation Record · LEDGER

Flaws of ImageNet, Computer Vision's Favourite Dataset

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2412.00076.

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

pith.paper-citation-record.v1
2412.00076 v1

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 2026-08-11T06:34:44.6726+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T04:46:35.237981Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T06:16:19.390415Z

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 eb35cc0e-ada6-415c-b58e-8e1f9d5e6066 · inbound

The Impact of the Single-Label Assumption in Image Recognition Benchmarking cites this paper.

The Impact of the Single-Label Assumption in Image Recognition Benchmarking Flaws of ImageNet, Computer Vision's Favourite Dataset

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-08-11T04:46:35.547312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T04:46:35.237981Z digest=sha256:d65b07c4b8825d756c5c49c1d3eb80bca4978a13cd616d8f9b823667497176df

Observation 383cb299-c875-43f8-9a69-2540bcbbd859 · inbound

Why Domain Matters: Domain-Aware Benchmarking of Underwater Object Detection and Annotation Quality cites this paper.

Why Domain Matters: Domain-Aware Benchmarking of Underwater Object Detection and Annotation Quality Flaws of ImageNet, Computer Vision's Favourite Dataset

Reference 13

Resolution
unresolved
no resolver link, observed 2026-07-14T10:43:35.408579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T10:43:35.408579Z digest=sha256:67a0f037f9c8c17eda70026145c6b6c3e44ddd3cd6027501bddf28d5681809e2