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Paper Citation Record · LEDGER

Robust Counterfactual Explanations in Machine Learning: A Survey

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2402.01928.

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

pith.paper-citation-record.v1
2402.01928 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:11:31.744514Z

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

2
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 2481ddfb-627a-47e5-a9b6-f920b8213a97 · inbound

Robust Counterfactual Explanations under Model Multiplicity Using Multi-Objective Optimization cites this paper.

Robust Counterfactual Explanations under Model Multiplicity Using Multi-Objective Optimization Robust Counterfactual Explanations in Machine Learning: A Survey

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-10T21:11:31.744514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:11:31.744514Z digest=sha256:c10a59471adedf1f9562f9598a8b9904353f59709e5e0ffbebc55a4166c93fe9

Observation 2add08e3-f577-47a2-8898-2da5eef7d54c · inbound

Faster Verified Explanations for Neural Networks cites this paper.

Faster Verified Explanations for Neural Networks Robust Counterfactual Explanations in Machine Learning: A Survey

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-17T03:31:28.440858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-17T03:31:10.191431Z digest=sha256:985429353dd40247c1d36b59760ba5128758ea004ceb834f79eeb5f236e1728d

Observation 5a9696f6-2354-419a-96fb-a47813e0f5eb · inbound

Faster Verified Explanations for Neural Networks cites this paper.

Faster Verified Explanations for Neural Networks Robust Counterfactual Explanations in Machine Learning: A Survey

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-17T03:31:28.418141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-17T03:31:10.191431Z digest=sha256:cde33eb6c6aaf6923d61212b5a9f32fdf1de19cfab4a3ee3a9f1643b90a140f3

Observation 729b5a1d-c60a-4b28-83f0-36b0aa5c5dba · inbound

Towards Verified and Targeted Explanations through Formal Methods cites this paper.

Towards Verified and Targeted Explanations through Formal Methods Robust Counterfactual Explanations in Machine Learning: A Survey

Reference 25

Resolution
unresolved
no resolver link, observed 2026-07-13T11:54:05.610252Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T11:54:05.610252Z digest=sha256:1e8c78d0399e5a79330a27082eb741254d25d305e0a4ad6417da3a37c20add18

Observation d5928477-4156-4474-9fa4-b5c6affb939e · inbound

Profit-Based Counterfactual Explanations for Product Improvement: A Case Study of Manga Sales in Japan cites this paper.

Profit-Based Counterfactual Explanations for Product Improvement: A Case Study of Manga Sales in Japan Robust Counterfactual Explanations in Machine Learning: A Survey

Reference 16

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T14:58:32.467474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-03T14:52:10.546438Z digest=sha256:18a42d833ed076e9da1e255609ad38b137fdb27aafecd4c4aa3ed29493c3cf63