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Paper Citation Record · LEDGER

Distribution Density, Tails, and Outliers in Machine Learning: Metrics and Applications

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1910.13427.

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

pith.paper-citation-record.v1
1910.13427 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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T14:40:50.103273Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-08T14:40:50.377842Z

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 5a7c8717-2cf8-4690-b485-71f668df23a1 · inbound

FairDropout: Using Example-Tied Dropout to Enhance Generalization of Minority Groups cites this paper.

FairDropout: Using Example-Tied Dropout to Enhance Generalization of Minority Groups Distribution Density, Tails, and Outliers in Machine Learning: Metrics and Applications

Reference 2019

Resolution
verified exact
local_arxiv, observed 2026-08-08T14:40:50.384145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T14:40:50.103273Z digest=sha256:52d0a11f879b25eeeaaf7335a7f6128a9cca55c004e6c43ee5f826b330462017

Observation fc076f7f-2ea3-4736-8466-01ef2336da90 · inbound

Benchmarking Unlearning for Vision Transformers cites this paper.

Benchmarking Unlearning for Vision Transformers Distribution Density, Tails, and Outliers in Machine Learning: Metrics and Applications

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-02T21:27:38.210726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T21:27:38.210726Z digest=sha256:dd26580ea613f4e83a7c5bcca62d9718981a1ad3d1a8c85b7ae92f7b1709445b