Paper Citation Record · LEDGER

Efficient Contrastive Explanations on Demand

As of 15 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 0 inbound Pith citation observations 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

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

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

51 of 51 outbound references displayed

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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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This paper cites Extracting MUCs from constraint networks.

Efficient Contrastive Explanations on Demand Extracting MUCs from constraint networks

Reference 12

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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

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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

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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

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Efficient Contrastive Explanations on Demand Minimal sets on propositional formulae

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

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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

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

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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

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

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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

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Pith citing papers

No inbound Pith citation observations are available.