Paper Citation Record · LEDGER

Optimized Instance Alteration for Explaining and Assessing Robustness of Classifiers

As of 18 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2607.06637.

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

pith.paper-citation-record.v1
2607.06637 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-11T00:49:25.369674Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

24 of 24 outbound references displayed

verified exact3
verified fuzzy20
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ac3dc3fc-28e4-4e50-8281-4c4bbe7478c7 · outbound

This paper cites Counterfactual explanations without opening the black box: Automated decisions and the gdpr,.

Optimized Instance Alteration for Explaining and Assessing Robustness of Classifiers Counterfactual explanations without opening the black box: Automated decisions and the gdpr,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T00:57:44.958955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c4c4d527-5d0c-4ae6-bf0f-40f73c42b8b7 · outbound

This paper cites Desiderata for interpretable explanations: Quantifying interpretability of explanations,.

Optimized Instance Alteration for Explaining and Assessing Robustness of Classifiers Desiderata for interpretable explanations: Quantifying interpretability of explanations,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T00:57:44.978773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 63b3fab5-d8c0-4195-9f1b-c2e8e65f1678 · outbound

This paper cites Multi-objective counter- factual explanations,.

Optimized Instance Alteration for Explaining and Assessing Robustness of Classifiers Multi-objective counter- factual explanations,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T00:57:44.998408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ab88c477-7902-443b-a4eb-3d24d9902966 · outbound

This paper cites Inverse Classification for Comparison-based Interpretability in Machine Learning.

Optimized Instance Alteration for Explaining and Assessing Robustness of Classifiers Inverse Classification for Comparison-based Interpretability in Machine Learning

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-07-11T00:57:42.274269Z

Source-reported events for the cited work

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Observation 879d7cdd-8db3-44d5-80b4-5ec163358f98 · outbound

This paper cites Explaining and harnessing adversarial examples.

Optimized Instance Alteration for Explaining and Assessing Robustness of Classifiers Explaining and harnessing adversarial examples

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T00:57:44.888233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 214a9362-cf52-4dc6-86df-1dde4b879bb2 · outbound

This paper cites Towards deep learning models resistant to adversarial attacks.

Optimized Instance Alteration for Explaining and Assessing Robustness of Classifiers Towards deep learning models resistant to adversarial attacks

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T00:57:44.976964Z

Source-reported events for the cited work

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Observation c42dbd14-83c8-4541-bef4-77c005e8596b · outbound

This paper cites Certified adversarial robustness via randomized smoothing,.

Optimized Instance Alteration for Explaining and Assessing Robustness of Classifiers Certified adversarial robustness via randomized smoothing,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T00:57:45.141505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f36ac42e-d352-4c90-83d3-5013194dabef · outbound

This paper cites Counterfactual explanations and algorithmic recourses for machine learning: A review.

Optimized Instance Alteration for Explaining and Assessing Robustness of Classifiers Counterfactual explanations and algorithmic recourses for machine learning: A review

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T00:57:45.167289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 321dedd3-e2e1-41cb-9730-022fe873e88c · outbound

This paper cites Algorithmic recourse: from counterfactual explanations to interventions,.

Optimized Instance Alteration for Explaining and Assessing Robustness of Classifiers Algorithmic recourse: from counterfactual explanations to interventions,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T00:57:44.958237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8d5b7ef6-a3dd-481b-8150-1c521e77dc7b · outbound

This paper cites Counterfactual explanations and algorithmic recourses for machine learning: A review,.

Optimized Instance Alteration for Explaining and Assessing Robustness of Classifiers Counterfactual explanations and algorithmic recourses for machine learning: A review,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T00:57:45.147469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 61edd8a2-1de1-4213-8b78-f9792ad6e8b5 · outbound

This paper cites 2024 , issue_date =.

Optimized Instance Alteration for Explaining and Assessing Robustness of Classifiers 2024 , issue_date =

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d7c61f36-7631-4d64-881d-497e5698e750 · outbound

This paper cites Explaining machine learning classifiers through diverse counterfactual explanations.

Optimized Instance Alteration for Explaining and Assessing Robustness of Classifiers Explaining machine learning classifiers through diverse counterfactual explanations

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T00:57:45.176957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a395affc-c479-4a77-9751-497608594e9f · outbound

This paper cites Getting a CLUE: A Method for Explaining Uncertainty Estimates.

Optimized Instance Alteration for Explaining and Assessing Robustness of Classifiers Getting a CLUE: A Method for Explaining Uncertainty Estimates

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-07-11T00:57:42.293183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b9d6aec1-56cd-496a-9b7d-e2a5e0f91331 · outbound

This paper cites Towards Realistic Individual Recourse and Actionable Explanations in Black-Box Decision Making Systems.

Optimized Instance Alteration for Explaining and Assessing Robustness of Classifiers Towards Realistic Individual Recourse and Actionable Explanations in Black-Box Decision Making Systems

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-07-11T00:57:42.312566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 828dab44-ded3-4c72-99f4-f820de0c54d5 · outbound

This paper cites Interpretable counterfactual explana- tions guided by prototypes,.

Optimized Instance Alteration for Explaining and Assessing Robustness of Classifiers Interpretable counterfactual explana- tions guided by prototypes,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T00:57:45.158392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 75622c2c-4ea1-48cd-bbe9-34639b536cf6 · outbound

This paper cites Model selection and estimation in regression with grouped variables.

Optimized Instance Alteration for Explaining and Assessing Robustness of Classifiers Model selection and estimation in regression with grouped variables

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T00:57:45.124868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 67496f19-2445-4a06-8522-6ad67c808fcd · outbound

This paper cites Sparsity and smoothness via the fused lasso,.

Optimized Instance Alteration for Explaining and Assessing Robustness of Classifiers Sparsity and smoothness via the fused lasso,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T00:57:45.218872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 42741049-f699-4181-bbe4-2fe3bf1a5f38 · outbound

This paper cites Multivariate regression with grouped variables: Modeling and estimation via sparse graphical mod- els,.

Optimized Instance Alteration for Explaining and Assessing Robustness of Classifiers Multivariate regression with grouped variables: Modeling and estimation via sparse graphical mod- els,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T00:57:45.067552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2a4b63e7-cbaa-4da8-b006-01dda045a653 · outbound

This paper cites A tutorial on spectral clustering,.

Optimized Instance Alteration for Explaining and Assessing Robustness of Classifiers A tutorial on spectral clustering,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T00:57:45.106798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6d554f09-690a-413c-94e0-4602ae8715fc · outbound

This paper cites Modularity and community structure in networks,.

Optimized Instance Alteration for Explaining and Assessing Robustness of Classifiers Modularity and community structure in networks,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T00:57:45.128808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 9ea0ec49-3de5-42f1-8463-c92162a97bdb · outbound

This paper cites Holistically-nested edge detection.

Optimized Instance Alteration for Explaining and Assessing Robustness of Classifiers Holistically-nested edge detection

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T00:57:45.067127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e0c972df-fc0a-43ac-9d84-51b992b629c4 · outbound

This paper cites Explanations based on the missing: Towards contrastive explanations with pertinent negatives.

Optimized Instance Alteration for Explaining and Assessing Robustness of Classifiers Explanations based on the missing: Towards contrastive explanations with pertinent negatives

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T00:57:45.185632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation bf4bc568-9146-4788-a931-c180b49543fd · outbound

This paper cites Explainable image classification with evidence counter- factual,.

Optimized Instance Alteration for Explaining and Assessing Robustness of Classifiers Explainable image classification with evidence counter- factual,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T00:57:45.209037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7f881eec-4d4d-4a0c-95ec-2057154d687d · outbound

This paper cites He was General Chair for the 2001 IEEE Workshop on Neural Networks for Signal Processing.

Optimized Instance Alteration for Explaining and Assessing Robustness of Classifiers He was General Chair for the 2001 IEEE Workshop on Neural Networks for Signal Processing

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T00:57:45.195093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

No inbound Pith citation observations are available.