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Paper Citation Record · LEDGER

Enhancing the Interpretability of Rule-based Explanations through Information Retrieval

As of 14 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2507.05976.

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

pith.paper-citation-record.v1
2507.05976 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:18:53.831885Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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

30 of 30 outbound references displayed

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  • verified fuzzy26
  • unresolved4
  • parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation eba83696-7965-45f2-9e6e-211027ab689f · outbound

This paper cites The importance of interpretability and visualization in machine learning for applications in medicine and health care.

Enhancing the Interpretability of Rule-based Explanations through Information Retrieval The importance of interpretability and visualization in machine learning for applications in medicine and health care

Reference 1

Resolution
verified fuzzy
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Observation 6fdbc719-d0c5-492d-95b0-c6486f6fbdcd · outbound

This paper cites an unresolved cited work.

Enhancing the Interpretability of Rule-based Explanations through Information Retrieval Unresolved cited work

Reference 2

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Source-reported events for the cited work

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Observation b7e39945-cd18-4834-be6a-2edcbe196d9f · outbound

This paper cites Markus, Jan A.

Enhancing the Interpretability of Rule-based Explanations through Information Retrieval Markus, Jan A

Reference 3

Resolution
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Source-reported events for the cited work

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Observation 2ab6b73b-8524-4a1f-a8f4-b32066e57a7d · outbound

This paper cites Causability and explainability of artificial intelligence in medicine.

Enhancing the Interpretability of Rule-based Explanations through Information Retrieval Causability and explainability of artificial intelligence in medicine

Reference 4

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation e70c5156-e90c-4ac2-b7ae-65e8edd24762 · outbound

This paper cites What do we want from explainable artificial intelligence (xai)? – a stakeholder perspective on xai and a conceptual model guiding interdisciplinary xai research.

Enhancing the Interpretability of Rule-based Explanations through Information Retrieval What do we want from explainable artificial intelligence (xai)? – a stakeholder perspective on xai and a conceptual model guiding interdisciplinary xai research

Reference 5

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation e11ccee7-2683-4721-adb6-c8cab18801d7 · outbound

This paper cites black box.

Enhancing the Interpretability of Rule-based Explanations through Information Retrieval black box

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation ce39b517-e131-4517-b732-5a3d1fdde0f0 · outbound

This paper cites McCradden, and Anna Goldenberg.

Enhancing the Interpretability of Rule-based Explanations through Information Retrieval McCradden, and Anna Goldenberg

Reference 7

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation ca4eeb68-df26-42c4-b361-2b7781323f25 · outbound

This paper cites Explainable ai (xai): A systematic meta-survey of current challenges and future opportunities.

Enhancing the Interpretability of Rule-based Explanations through Information Retrieval Explainable ai (xai): A systematic meta-survey of current challenges and future opportunities

Reference 8

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation f44f29c2-cada-46a7-a1a7-5e1ffd9f66cf · outbound

This paper cites Methods for interpreting and understanding deep neural networks.

Enhancing the Interpretability of Rule-based Explanations through Information Retrieval Methods for interpreting and understanding deep neural networks

Reference 9

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 9814fa74-13ef-4bae-87b3-7000a11a4f3f · outbound

This paper cites Moore, Marinka Zitnik, and John H.

Enhancing the Interpretability of Rule-based Explanations through Information Retrieval Moore, Marinka Zitnik, and John H

Reference 10

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation a472d593-6cd6-487a-a1ae-e6194d3990d9 · outbound

This paper cites Fidex: An algorithm for the explainability of ensembles and svms.

Enhancing the Interpretability of Rule-based Explanations through Information Retrieval Fidex: An algorithm for the explainability of ensembles and svms

Reference 11

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 6a416185-f348-4e60-bcd6-f5cf92d8d11e · outbound

This paper cites Research challenges in trustworthy artificial intelligence and computing for health: The case of the pre-act project.

Enhancing the Interpretability of Rule-based Explanations through Information Retrieval Research challenges in trustworthy artificial intelligence and computing for health: The case of the pre-act project

Reference 12

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 99e6e4b1-d1d0-4b2d-bb82-de3e85dfed7f · outbound

This paper cites Madai, and the Precise4Q consortium.

Enhancing the Interpretability of Rule-based Explanations through Information Retrieval Madai, and the Precise4Q consortium

Reference 13

Resolution
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Source-reported events for the cited work

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Observation c9056261-92d8-4df5-beb3-b6a9482664af · outbound

This paper cites Incidence and risk factors of lymphedema after breast cancer treatment: 10 years of follow-up.

Enhancing the Interpretability of Rule-based Explanations through Information Retrieval Incidence and risk factors of lymphedema after breast cancer treatment: 10 years of follow-up

Reference 14

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 99aee656-dd13-4e07-8516-7e31c423a2e7 · outbound

This paper cites Incidence and risk factors of breast cancer lymphoedema.

Enhancing the Interpretability of Rule-based Explanations through Information Retrieval Incidence and risk factors of breast cancer lymphoedema

Reference 15

Resolution
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Source-reported events for the cited work

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Observation 0e15e5c6-bf30-44b5-8800-4e2c13c3db9f · outbound

This paper cites Statistical power analyses using g*power 3.1: Tests for correlation and regression analyses.

Enhancing the Interpretability of Rule-based Explanations through Information Retrieval Statistical power analyses using g*power 3.1: Tests for correlation and regression analyses

Reference 16

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 264b24f6-1374-4c92-96b0-e885ac768f1d · outbound

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Enhancing the Interpretability of Rule-based Explanations through Information Retrieval Unresolved cited work

Reference 17

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Source-reported events for the cited work

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Observation f5421bdb-30ec-43d4-bfe6-a52710af45e5 · outbound

This paper cites Exploring multi-task learning for explainability.

Enhancing the Interpretability of Rule-based Explanations through Information Retrieval Exploring multi-task learning for explainability

Reference 18

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Source-reported events for the cited work

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Observation e5ddf5d8-d6c0-409f-9327-bf58b52a9283 · outbound

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Enhancing the Interpretability of Rule-based Explanations through Information Retrieval Lundberg and Su-In Lee

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation a4c1b774-f9ff-4c34-b472-31cbc6cf0c0e · outbound

This paper cites Why Should I Trust You?.

Enhancing the Interpretability of Rule-based Explanations through Information Retrieval Why Should I Trust You?

Reference 20

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Enhancing the Interpretability of Rule-based Explanations through Information Retrieval Analysis of regression in game theory approach

Reference 21

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Source-reported events for the cited work

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Observation 69e534f8-df57-4cdd-85b6-f064ebf2f901 · outbound

This paper cites Explaining prediction models and individual predictions with feature contributions.

Enhancing the Interpretability of Rule-based Explanations through Information Retrieval Explaining prediction models and individual predictions with feature contributions

Reference 22

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Source-reported events for the cited work

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Observation 6bdba078-6ee0-4e27-9159-2b1dc6a47500 · outbound

This paper cites Covert, Scott M.

Enhancing the Interpretability of Rule-based Explanations through Information Retrieval Covert, Scott M

Reference 23

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation bc101971-97ee-4c6f-8bb4-120b048e13d3 · outbound

This paper cites Learning important features through propagating activation differences.

Enhancing the Interpretability of Rule-based Explanations through Information Retrieval Learning important features through propagating activation differences

Reference 24

Resolution
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Source-reported events for the cited work

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Observation 3c44f858-bdfa-490c-a9a2-5526352f56f1 · outbound

This paper cites On pixel-wise explanations for non-linear classifier decisions by layer-wise relevance propagation.

Enhancing the Interpretability of Rule-based Explanations through Information Retrieval On pixel-wise explanations for non-linear classifier decisions by layer-wise relevance propagation

Reference 25

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 143dc3a1-ea5a-475a-bfdb-a69b1f552fc5 · outbound

This paper cites A holistic approach to interpretability in financial lending: Models, visualizations, and summary-explanations.

Enhancing the Interpretability of Rule-based Explanations through Information Retrieval A holistic approach to interpretability in financial lending: Models, visualizations, and summary-explanations

Reference 26

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 1e6c02b9-ac0d-46d0-8cfa-95ae8cb08bd0 · outbound

This paper cites Developing a catalogue of explainability methods to support expert and non-expert users.

Enhancing the Interpretability of Rule-based Explanations through Information Retrieval Developing a catalogue of explainability methods to support expert and non-expert users

Reference 27

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 19a70c1e-d7eb-427b-a7d1-8408ff71a28f · outbound

This paper cites Explainability in nlp model: Detection of covid-19 twitter fake news.

Enhancing the Interpretability of Rule-based Explanations through Information Retrieval Explainability in nlp model: Detection of covid-19 twitter fake news

Reference 28

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation d0321c5c-3667-488b-a301-dcb609d66824 · outbound

This paper cites Sparkly: A simple yet surprisingly strong tf/idf blocker for entity matching.

Enhancing the Interpretability of Rule-based Explanations through Information Retrieval Sparkly: A simple yet surprisingly strong tf/idf blocker for entity matching

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:18:54.021366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 626dcf05-c338-4654-b8a8-4aeaca4cb722 · outbound

This paper cites an unresolved cited work.

Enhancing the Interpretability of Rule-based Explanations through Information Retrieval Unresolved cited work

Reference 2016

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Pith citing papers

No inbound Pith citation observations are available.