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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 2026-08-16T06:30:59.297886+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=sha256:2809e87dac0a86c34d883273a64a93137bdc00ea45d9c642641ba725334c904a

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-17T03:31:10.191431Z digest=sha256:0b7cc12fde9b5e17fcb9130057234941cfb104559c5a61dbc292d712640c6f5e

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-17T03:31:10.191431Z digest=sha256:30b63547a90ba00ed320b34da3608446752c0f0593da5f26c2ed91b6623187f2

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=sha256:3b37ebee71b315106783e62859a894144999aeaffe2fa41b5932dd8fd2399ba8

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-07-03T14:52:10.546438Z digest=sha256:63f6464df659bbcfdbd8a035a80012e3fe6541a2c6838940754311ebf29cc40f