Paper Citation Record · LEDGER

Techniques for Interpretable Machine Learning

As of 24 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1808.00033.

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

pith.paper-citation-record.v1
1808.00033 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T14:44:50.003790Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-05-25T19:06:09.180945Z

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 21288d4e-d075-4805-abf7-b49d2d2cdb0a · inbound

Unexplainability and Incomprehensibility of Artificial Intelligence cites this paper.

Unexplainability and Incomprehensibility of Artificial Intelligence Techniques for Interpretable Machine Learning

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-05-25T19:06:09.183240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0c8f4a39-af02-4dac-a22f-f8f5757fbd1b · inbound

The Mass, Fake News, and Cognition Security cites this paper.

The Mass, Fake News, and Cognition Security Techniques for Interpretable Machine Learning

Reference 149

Resolution: verified exact; local_arxiv, observed 2026-05-24T23:50:05.560167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3221e870-124e-43d0-bd8a-fcbdd65a70e0 · inbound

Interpretable and Fine-Grained Visual Explanations for Convolutional Neural Networks cites this paper.

Interpretable and Fine-Grained Visual Explanations for Convolutional Neural Networks Techniques for Interpretable Machine Learning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-14T14:44:50.003790Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cbbcca3f-08bb-4e27-9163-4ce3f356f45a · inbound

Machine Theory of Mind for Autonomous Cyber-Defence cites this paper.

Machine Theory of Mind for Autonomous Cyber-Defence Techniques for Interpretable Machine Learning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T21:34:38.620630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.