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Paper Citation Record · LEDGER

Human-interpretable model explainability on high-dimensional data

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2010.07384.

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

pith.paper-citation-record.v1
2010.07384 v2

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 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T17:46:47.268737Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T09:10:59.356382Z

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 d7be270d-18d7-4613-a663-bcccdcd708f2 · inbound

Strategies and Challenges of Efficient White-Box Training for Human Activity Recognition cites this paper.

Strategies and Challenges of Efficient White-Box Training for Human Activity Recognition Human-interpretable model explainability on high-dimensional data

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-11T17:46:47.268737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T17:46:47.268737Z digest=sha256:166819f5457c11f0ac40246fc4cff6339fb708710d43cc4c5db97d37c200f247

Observation 43035fff-e56d-479c-af3c-8e80875cf544 · inbound

ShapShift: Explaining Model Prediction Shifts with Subgroup Conditional Shapley Values cites this paper.

ShapShift: Explaining Model Prediction Shifts with Subgroup Conditional Shapley Values Human-interpretable model explainability on high-dimensional data

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-11T09:10:59.359359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-10T16:13:22.301367Z digest=sha256:cfc81b4b39a36f745f8fca4d238d583330a289ed9e88809945af20b7c04f9d76