Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Counterfactual Explanations for Machine Learning: Challenges Revisited
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2106.07756.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T15:00:06.549018Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-20T07:38:09.548933Z
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 7b8157c5-62b3-466c-9148-f92b62ee2749 · inbound
Tabular Diffusion based Actionable Counterfactual Explanations for Network Intrusion Detection cites this paper.
Tabular Diffusion based Actionable Counterfactual Explanations for Network Intrusion Detection Counterfactual Explanations for Machine Learning: Challenges Revisited
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:00:06.549018Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bce69013-8ffa-4beb-b043-f40396a1ce04 · inbound
Data and AI governance: Promoting equity, ethics, and fairness in large language models cites this paper.
Data and AI governance: Promoting equity, ethics, and fairness in large language models Counterfactual Explanations for Machine Learning: Challenges Revisited
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T01:03:24.036661Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1b96e825-1014-4841-a6c6-0f6cfe7d220e · inbound
ExECG: An Explainable AI Framework for ECG models cites this paper.
ExECG: An Explainable AI Framework for ECG models Counterfactual Explanations for Machine Learning: Challenges Revisited
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T07:38:09.551187Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.