Paper Citation Record · LEDGER

Re-Visiting Explainable AI Evaluation Metrics to Identify The Most Informative Features

As of 19 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 0 inbound Pith citation observations for arXiv:2502.00088.

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

pith.paper-citation-record.v1
2502.00088 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T20:40:01.017003Z

measured 12 of 12 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

12 of 12 outbound references displayed

verified exact0
verified fuzzy10
unresolved2
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 23a5d89f-c486-4a0f-8c04-d5d77705d367 · outbound

This paper cites Notions of explainability and evaluation approaches for explainable artifi- cial intelligence.

Re-Visiting Explainable AI Evaluation Metrics to Identify The Most Informative Features Notions of explainability and evaluation approaches for explainable artifi- cial intelligence

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T20:40:01.241604Z

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.

Observation 25ca49ed-e172-4428-8931-338d833f166f · outbound

This paper cites A review of evaluation approaches for explainable AI with applications in cardiol- ogy.

Re-Visiting Explainable AI Evaluation Metrics to Identify The Most Informative Features A review of evaluation approaches for explainable AI with applications in cardiol- ogy

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T20:40:01.225730Z

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.

Observation 171f6e4c-2c82-450d-adbd-b465e306155f · outbound

This paper cites A benchmark for interpretability methods in deep neural networks.

Re-Visiting Explainable AI Evaluation Metrics to Identify The Most Informative Features A benchmark for interpretability methods in deep neural networks

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T20:40:01.209378Z

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.

Observation e2f810a0-bf05-439f-a9fc-1c9e0a5bb6f7 · outbound

This paper cites Multilayer Perceptron of Software Complexity Metrics for Explainable Multi- collinearity Mitigation and Defect Localization.

Re-Visiting Explainable AI Evaluation Metrics to Identify The Most Informative Features Multilayer Perceptron of Software Complexity Metrics for Explainable Multi- collinearity Mitigation and Defect Localization

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T20:40:01.193165Z

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.

Observation e76f9f62-5abb-411b-a102-63ccc59bea20 · outbound

This paper cites A Unified Approach to Interpreting Model Predictions.

Re-Visiting Explainable AI Evaluation Metrics to Identify The Most Informative Features A Unified Approach to Interpreting Model Predictions

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-09T20:40:00.983678Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99b86c28-95b2-496b-b43e-1d9c7fe33614 · outbound

This paper cites Characterizing the Contribution of Dependent Features in XAI Methods.

Re-Visiting Explainable AI Evaluation Metrics to Identify The Most Informative Features Characterizing the Contribution of Dependent Features in XAI Methods

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T20:40:01.176631Z

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.

Observation 9076880c-30e4-400b-af7e-edc06ad44d11 · outbound

This paper cites Permutation importance: a corrected feature importance measure.

Re-Visiting Explainable AI Evaluation Metrics to Identify The Most Informative Features Permutation importance: a corrected feature importance measure

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T20:40:01.159618Z

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.

Observation 3bc04053-532b-440b-89f5-26a72795ed70 · outbound

This paper cites CDC National Health Report: leading causes of morbidity and mortality and associated behavioral risk and protective factors–United States, 2005-2013.

Re-Visiting Explainable AI Evaluation Metrics to Identify The Most Informative Features CDC National Health Report: leading causes of morbidity and mortality and associated behavioral risk and protective factors–United States, 2005-2013

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T20:40:01.143123Z

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.

Observation 02e7ece6-adf2-4144-a88f-4aa7d5cb3bc0 · outbound

This paper cites Modeling wine preferences by data mining from physicochemical properties.

Re-Visiting Explainable AI Evaluation Metrics to Identify The Most Informative Features Modeling wine preferences by data mining from physicochemical properties

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T20:40:01.123471Z

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.

Observation 26453df1-a54e-44f2-8f6d-4d56114c72c7 · outbound

This paper cites Efficient Saliency Maps for Explainable AI.

Re-Visiting Explainable AI Evaluation Metrics to Identify The Most Informative Features Efficient Saliency Maps for Explainable AI

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-09T20:40:01.007693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48828727-9ba1-48f7-a7a0-4d3616c3ecaf · outbound

This paper cites Explainable artificial intelligence approaches: Challenges and perspectives.

Re-Visiting Explainable AI Evaluation Metrics to Identify The Most Informative Features Explainable artificial intelligence approaches: Challenges and perspectives

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T20:40:01.107310Z

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.

Observation 6ec06455-6933-4c1f-8b76-4ec39513523a · outbound

This paper cites Cardiovascular risk factors and physical activity for the prevention of cardiovas- cular diseases in the elderly.

Re-Visiting Explainable AI Evaluation Metrics to Identify The Most Informative Features Cardiovascular risk factors and physical activity for the prevention of cardiovas- cular diseases in the elderly

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T20:40:01.090722Z

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.

Pith citing papers

No inbound Pith citation observations are available.