Paper Citation Record · LEDGER

Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:1811.10154.

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

pith.paper-citation-record.v1
1811.10154 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:43:45.604891Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

44
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation eb490f62-e530-444e-96c8-e3ef34cd3ecf · inbound

Attention is not not Explanation cites this paper.

Attention is not not Explanation Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-14T13:41:39.374810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e47dbb16-4411-4c90-bf4f-f1d2b137a950 · inbound

SIRUS: Stable and Interpretable RUle Set for Classification cites this paper.

SIRUS: Stable and Interpretable RUle Set for Classification Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-14T12:39:47.679201Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 466f3672-3f5e-447b-a785-b2999ebce4c5 · inbound

"All that Glitters": Approaches to Evaluations with Unreliable Model and Human Annotations cites this paper.

"All that Glitters": Approaches to Evaluations with Unreliable Model and Human Annotations Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead

Reference 115

Resolution: unresolved; no resolver link, observed 2026-08-12T14:14:09.253511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 007bcd9a-38cb-444e-bc77-673eeb4abe80 · inbound

Comparative Analysis of Black-Box and White-Box Machine Learning Model in Phishing Detection cites this paper.

Comparative Analysis of Black-Box and White-Box Machine Learning Model in Phishing Detection Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-11T23:52:56.508484Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77bcbc21-81a9-4cae-94d7-905506c35fda · inbound

The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations cites this paper.

The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-10T21:26:52.734657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3b5abdd8-36a2-4c5f-b059-bf60fb302c5c · inbound

Self-Ablating Transformers: More Interpretability, Less Sparsity cites this paper.

Self-Ablating Transformers: More Interpretability, Less Sparsity Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-16T04:43:45.604891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8de9b13-d561-481f-9c11-3a1b50f80d47 · inbound

AlphaEval: A Comprehensive and Efficient Evaluation Framework for Formula Alpha Mining cites this paper.

AlphaEval: A Comprehensive and Efficient Evaluation Framework for Formula Alpha Mining Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-05T22:18:08.926791Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d71ac66-a59f-4c07-a1a9-ae4fe7c1d177 · inbound

Interpretable machine learning of halo gas density profiles: a sensitivity analysis of cosmological hydrodynamical simulations cites this paper.

Interpretable machine learning of halo gas density profiles: a sensitivity analysis of cosmological hydrodynamical simulations Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-03T17:35:17.791028Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c0cb1a0-c856-4ede-bce8-af1ce930e815 · inbound

MedFormer-UR: Uncertainty-Routed Transformer for Medical Image Classification cites this paper.

MedFormer-UR: Uncertainty-Routed Transformer for Medical Image Classification Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead

Reference 6

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T06:11:03.208142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e146dd14-54cd-49f3-ac28-90f8c0580e37 · inbound

Scale-Aware Adversarial Analysis: A Diagnostic for Generative AI in Multiscale Complex Systems cites this paper.

Scale-Aware Adversarial Analysis: A Diagnostic for Generative AI in Multiscale Complex Systems Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead

Reference 77

Resolution: verified exact; arxiv_id, observed 2026-05-09T19:56:16.581827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8f327af4-4234-40d9-bf06-c5530906f95f · inbound

Agentic-imodels: Evolving agentic interpretability tools via autoresearch cites this paper.

Agentic-imodels: Evolving agentic interpretability tools via autoresearch Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead

Reference 8

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T23:36:36.309204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 18365b0b-4c15-498a-8fb3-d1d22900885e · inbound

Staging by the Book: Automatic Sleep Stage Classification Using Scoring Rules cites this paper.

Staging by the Book: Automatic Sleep Stage Classification Using Scoring Rules Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-05-25T06:26:41.274992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 50c92403-3b56-4f91-a84d-cd76d2b2f986 · inbound

Beyond Explaining Predictions: Logic-Based Explanations for Confidence in Machine Learning Models cites this paper.

Beyond Explaining Predictions: Logic-Based Explanations for Confidence in Machine Learning Models Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead

Reference 27

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T03:57:38.727962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d16bcabe-80da-4228-91d0-e02ed35b9b94 · inbound

Foundation Models for Astrophysics cites this paper.

Foundation Models for Astrophysics Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead

Reference 112

Resolution: unresolved; no resolver link, observed 2026-08-04T04:31:49.020297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.