Paper Citation Record · LEDGER

Transparent AI: The Case for Interpretability and Explainability

As of 17 August 2026, this Paper Citation Record lists 5 of 5 outbound references and 1 inbound Pith citation observation for arXiv:2507.23535.

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

pith.paper-citation-record.v1
2507.23535 v1

Coverage vector

measured 5 of 5 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T10:45:59.623993Z

measured 6 of 6 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T13:05:33.225290Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T13:05:35.019258Z

Reference resolution

5 of 5 outbound references displayed

verified exact0
verified fuzzy2
unresolved1
parse uncertain0
malformed identifier1
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 37237e5b-8252-46a0-91c2-86e839c14d53 · outbound

This paper cites Sanity checks for saliency maps.

Transparent AI: The Case for Interpretability and Explainability Sanity checks for saliency maps

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:45:59.706439Z

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.

Observation 85ea4238-9f33-4982-a98b-7fe06301aea9 · outbound

This paper cites From Understanding to Utilization: A Survey on Explainability for Large Language Models.

Transparent AI: The Case for Interpretability and Explainability From Understanding to Utilization: A Survey on Explainability for Large Language Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T10:45:59.615953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 889d60a0-b336-46b0-8224-6366c3780aca · outbound

This paper cites Is Ignorance Bliss? The Role of Post Hoc Explanation Faithfulness and Alignment in Model Trust in Laypeople and Domain Experts.

Transparent AI: The Case for Interpretability and Explainability Is Ignorance Bliss? The Role of Post Hoc Explanation Faithfulness and Alignment in Model Trust in Laypeople and Domain Experts

Reference 31

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T10:45:59.682746Z

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.

Observation 15acfa93-16db-4e1e-b3b9-45ad79db4f1a · outbound

This paper cites Interpretable machine learning: Fundamental principles and 10 grand challenges.

Transparent AI: The Case for Interpretability and Explainability Interpretable machine learning: Fundamental principles and 10 grand challenges

Reference 42

Resolution: malformed identifier; no resolver link, observed 2026-08-06T10:45:59.620137Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 507c6f1b-f63c-4b33-84a4-37edca2b813c · outbound

This paper cites Evaluation of post-hoc interpretability methods in time-series classification.

Transparent AI: The Case for Interpretability and Explainability Evaluation of post-hoc interpretability methods in time-series classification

Reference 2673

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:45:59.695575Z

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.

Pith citing papers

Observation acc9d7b8-d6f1-49c1-8d49-78d4fdd6b2c2 · inbound

CoreThink: A Symbolic Reasoning Layer to reason over Long Horizon Tasks with LLMs cites this paper.

CoreThink: A Symbolic Reasoning Layer to reason over Long Horizon Tasks with LLMs Transparent AI: The Case for Interpretability and Explainability

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-08-05T13:05:35.041276Z

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.