Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Evaluating Explanation Without Ground Truth in Interpretable Machine Learning
As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1907.06831.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T15:56:17.681013Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-30T08:24:26.411389Z
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 d2e34ff0-179d-4709-928d-f16bda6e0e87 · inbound
Learning Credible Deep Neural Networks with Rationale Regularization cites this paper.
Learning Credible Deep Neural Networks with Rationale Regularization Evaluating Explanation Without Ground Truth in Interpretable Machine Learning
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T13:43:01.753992Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 86d4452d-26c7-4b7d-815a-1635c5ce6798 · inbound
Deep Learning-based Multi Project InP Wafer Simulation for Unsupervised Surface Defect Detection cites this paper.
Deep Learning-based Multi Project InP Wafer Simulation for Unsupervised Surface Defect Detection Evaluating Explanation Without Ground Truth in Interpretable Machine Learning
Reference 59
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T04:23:50.429163Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b9cb4a62-5156-4576-b5a4-2b0d7f0719bd · inbound
Is "Knowing It's Malicious Enough?" Evaluating LLMs for Fine-Grained Malware Behavior Auditing cites this paper.
Is "Knowing It's Malicious Enough?" Evaluating LLMs for Fine-Grained Malware Behavior Auditing Evaluating Explanation Without Ground Truth in Interpretable Machine Learning
Reference 55
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T15:56:17.681013Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a86208e8-df65-45e8-a5e6-8f2e50f419c7 · inbound
Improving Explanations: Applying the Feature Understandability Scale for Cost-Sensitive Feature Selection cites this paper.
Improving Explanations: Applying the Feature Understandability Scale for Cost-Sensitive Feature Selection Evaluating Explanation Without Ground Truth in Interpretable Machine Learning
Reference 66
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T00:15:54.290334Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation b6985732-4f3b-47a7-942f-29b69a7bb9f1 · inbound
Reliability, Faithfulness, and the Limits of Post-hoc Explanations of Opaque Scientific Models cites this paper.
Reliability, Faithfulness, and the Limits of Post-hoc Explanations of Opaque Scientific Models Evaluating Explanation Without Ground Truth in Interpretable Machine Learning
Reference 148
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T08:24:26.412836Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.