Paper Citation Record · LEDGER

Efficient Contrastive Explanations on Demand

As of 19 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 1 inbound Pith citation observation for arXiv:2412.18262.

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

pith.paper-citation-record.v1
2412.18262 v1

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T05:00:12.672136Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:07:54.618718Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-15T21:07:54.850299Z

Reference resolution

51 of 51 outbound references displayed

verified exact1
verified fuzzy39
unresolved11
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External citation measurements

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Outbound references

Observation 72b7de1e-9e32-404e-909e-c1837bf9275f · outbound

This paper cites Fathers of the deep learning revolution receive ACM A.

Efficient Contrastive Explanations on Demand Fathers of the deep learning revolution receive ACM A

Reference 1

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This paper cites British- C anadian AI expert G eoffrey H inton wins T uring award.

Efficient Contrastive Explanations on Demand British- C anadian AI expert G eoffrey H inton wins T uring award

Reference 2

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This paper cites 'godfather of ai' shares N obel physics prize.

Efficient Contrastive Explanations on Demand 'godfather of ai' shares N obel physics prize

Reference 3

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This paper cites Google D eep M ind boss wins N obel for proteins breakthrough.

Efficient Contrastive Explanations on Demand Google D eep M ind boss wins N obel for proteins breakthrough

Reference 4

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This paper cites Handbook of Satisfiability - Second Edition.

Efficient Contrastive Explanations on Demand Handbook of Satisfiability - Second Edition

Reference 5

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This paper cites Lobo, Vignesh Viswanathan, and Yair Zick.

Efficient Contrastive Explanations on Demand Lobo, Vignesh Viswanathan, and Yair Zick

Reference 6

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This paper cites Johnson, and Changliu Liu.

Efficient Contrastive Explanations on Demand Johnson, and Changliu Liu

Reference 7

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This paper cites Logic for explainable AI.

Efficient Contrastive Explanations on Demand Logic for explainable AI

Reference 8

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This paper cites The mnist database of handwritten digit images for machine learning research.

Efficient Contrastive Explanations on Demand The mnist database of handwritten digit images for machine learning research

Reference 9

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Efficient Contrastive Explanations on Demand Unresolved cited work

Reference 10

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This paper cites Gurobi Optimizer Reference Manual , 2023.

Efficient Contrastive Explanations on Demand Gurobi Optimizer Reference Manual , 2023

Reference 11

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Observation e6cd2cf0-1cc7-4224-912d-8c4b3a141250 · outbound

This paper cites Extracting MUCs from constraint networks.

Efficient Contrastive Explanations on Demand Extracting MUCs from constraint networks

Reference 12

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This paper cites Horn and Charles R.

Efficient Contrastive Explanations on Demand Horn and Charles R

Reference 13

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This paper cites From decision trees to explained decision sets.

Efficient Contrastive Explanations on Demand From decision trees to explained decision sets

Reference 14

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This paper cites From Robustness to Explainability and Back Again.

Efficient Contrastive Explanations on Demand From Robustness to Explainability and Back Again

Reference 15

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This paper cites On efficiently explaining graph-based classifiers.

Efficient Contrastive Explanations on Demand On efficiently explaining graph-based classifiers

Reference 16

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This paper cites SAT -based rigorous explanations for decision lists.

Efficient Contrastive Explanations on Demand SAT -based rigorous explanations for decision lists

Reference 17

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This paper cites Abduction-based explanations for machine learning models.

Efficient Contrastive Explanations on Demand Abduction-based explanations for machine learning models

Reference 18

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This paper cites From contrastive to abductive explanations and back again.

Efficient Contrastive Explanations on Demand From contrastive to abductive explanations and back again

Reference 19

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Efficient Contrastive Explanations on Demand Stuckey, and Jo \ a o Marques - Silva

Reference 20

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Efficient Contrastive Explanations on Demand Stuckey, and Jo \ a o Marques - Silva

Reference 21

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This paper cites On explaining random forests with SAT.

Efficient Contrastive Explanations on Demand On explaining random forests with SAT

Reference 22

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This paper cites On computing relevant features for explaining nbcs.

Efficient Contrastive Explanations on Demand On computing relevant features for explaining nbcs

Reference 23

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Efficient Contrastive Explanations on Demand On Explaining Decision Trees

Reference 24

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Efficient Contrastive Explanations on Demand On tackling explanation redundancy in decision trees

Reference 25

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This paper cites Provably Precise, Succinct and Efficient Explanations for Decision Trees.

Efficient Contrastive Explanations on Demand Provably Precise, Succinct and Efficient Explanations for Decision Trees

Reference 26

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Efficient Contrastive Explanations on Demand Cooper, and Jo \ a o Marques - Silva

Reference 27

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This paper cites Distance-Restricted Explanations: Theoretical Underpinnings & Efficient Implementation.

Efficient Contrastive Explanations on Demand Distance-Restricted Explanations: Theoretical Underpinnings & Efficient Implementation

Reference 28

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Efficient Contrastive Explanations on Demand Stuckey, and Jo \ a o Marques - Silva

Reference 29

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Efficient Contrastive Explanations on Demand Meel, and Jo \ a o Marques - Silva

Reference 30

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This paper cites From SHAP Scores to Feature Importance Scores.

Efficient Contrastive Explanations on Demand From SHAP Scores to Feature Importance Scores

Reference 31

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Efficient Contrastive Explanations on Demand On correcting SHAP scores

Reference 32

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Efficient Contrastive Explanations on Demand Liffiton, Alessandro Previti, Ammar Malik, and Jo \ a o Marques - Silva

Reference 33

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Efficient Contrastive Explanations on Demand Reasoning about inconsistent formulas

Reference 34

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Efficient Contrastive Explanations on Demand On computing minimal correction subsets

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Efficient Contrastive Explanations on Demand Minimal sets over monotone predicates in boolean formulae

Reference 36

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Efficient Contrastive Explanations on Demand Minimal sets on propositional formulae

Reference 37

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Efficient Contrastive Explanations on Demand Cooper, Alexey Ignatiev, and Nina Narodytska

Reference 38

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Efficient Contrastive Explanations on Demand Logic-based explainability in machine learning

Reference 39

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Efficient Contrastive Explanations on Demand Logic-based explainability: Past, present and future

Reference 40

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Efficient Contrastive Explanations on Demand Explanation in artificial intelligence: Insights from the social sciences

Reference 41

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This paper cites Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala.

Efficient Contrastive Explanations on Demand Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala

Reference 42

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Efficient Contrastive Explanations on Demand why should I trust you?

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Efficient Contrastive Explanations on Demand An introduction to abstract algebra

Reference 44

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Efficient Contrastive Explanations on Demand A symbolic approach to explaining bayesian network classifiers

Reference 45

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Efficient Contrastive Explanations on Demand VeriX: Towards Verified Explainability of Deep Neural Networks

Reference 47

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Efficient Contrastive Explanations on Demand On Formal Feature Attribution and Its Approximation

Reference 50

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Pith citing papers

Observation 8f7b95ec-9542-4db7-8bb7-84304ce1d27d · inbound

Most General Explanations of Tree Ensembles (Extended Version) cites this paper.

Most General Explanations of Tree Ensembles (Extended Version) Efficient Contrastive Explanations on Demand

Reference 24

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