Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Distribution Density, Tails, and Outliers in Machine Learning: Metrics and Applications
As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1910.13427.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T12:00:06.792433Z
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 72595844-b9df-4da8-84f2-b8db1d3c84b0 · inbound
FUNU: Boosting Machine Unlearning Efficiency by Filtering Unnecessary Unlearning cites this paper.
FUNU: Boosting Machine Unlearning Efficiency by Filtering Unnecessary Unlearning Distribution Density, Tails, and Outliers in Machine Learning: Metrics and Applications
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T12:00:06.792433Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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 2026-08-22T06:32:14.747728+00:00.
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.