Multi-criteria Rank-based Aggregation for Explainable AI | Paper Citation Record

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This paper cites Credit default risk prediction based on deep learning,.

Multi-criteria Rank-based Aggregation for Explainable AI Credit default risk prediction based on deep learning,

Reference 1

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Observation 36487788-48e3-4879-9ea8-7e6b2f548d50 · outbound

This paper cites Explaining anomalies detected by autoencoders using shapley additive explana- tions,.

Multi-criteria Rank-based Aggregation for Explainable AI Explaining anomalies detected by autoencoders using shapley additive explana- tions,

Reference 2

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Observation 7eeaf1e5-251a-40b2-b163-788745d602ad · outbound

This paper cites European union regulations on algorith- mic decision making and a “right to explanation.

Multi-criteria Rank-based Aggregation for Explainable AI European union regulations on algorith- mic decision making and a “right to explanation

Reference 3

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Observation 8c3d8159-3130-48d2-ac3b-0134e636f144 · outbound

This paper cites Explainable chronic kidney disease (ckd) prediction using deep learning and shapley additive explanations (shap),.

Multi-criteria Rank-based Aggregation for Explainable AI Explainable chronic kidney disease (ckd) prediction using deep learning and shapley additive explanations (shap),

Reference 4

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Observation 4bdd873c-7ee1-461f-965a-3298b87c4362 · outbound

This paper cites Discriminative feature attri- butions: Bridging post hoc explainability and inherent interpretability,.

Multi-criteria Rank-based Aggregation for Explainable AI Discriminative feature attri- butions: Bridging post hoc explainability and inherent interpretability,

Reference 5

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Observation 85adfa7e-07a9-4163-93d9-d7124822612a · outbound

This paper cites Explainability in Machine Learning: a Pedagogical Perspective.

Multi-criteria Rank-based Aggregation for Explainable AI Explainability in Machine Learning: a Pedagogical Perspective

Reference 6

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Observation 4f0b1fb5-7b2c-4b53-9dfc-5f0905a41e5f · outbound

This paper cites Interpretability and Explainability: A Machine Learning Zoo Mini-tour.

Multi-criteria Rank-based Aggregation for Explainable AI Interpretability and Explainability: A Machine Learning Zoo Mini-tour

Reference 7

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Observation ec04a64e-2ee8-42aa-bda6-7201fc2d0196 · outbound

This paper cites Clarity in complexity: how aggregating explanations re- solves the disagreement problem,.

Multi-criteria Rank-based Aggregation for Explainable AI Clarity in complexity: how aggregating explanations re- solves the disagreement problem,

Reference 8

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Observation 71dfbed9-8b04-43b0-84b1-189bd8b83668 · outbound

This paper cites Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead,.

Multi-criteria Rank-based Aggregation for Explainable AI Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead,

Reference 9

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Observation fc33f939-5319-4002-9284-4208845dd7ac · outbound

This paper cites The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective.

Multi-criteria Rank-based Aggregation for Explainable AI The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective

Reference 10

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Observation faafb3bc-fdad-45d7-ad36-17ed70e828bd · outbound

This paper cites Aggregating explanation methods for stable and robust explainability.

Multi-criteria Rank-based Aggregation for Explainable AI Aggregating explanation methods for stable and robust explainability

Reference 11

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Observation 9c9c8f4d-5fa4-4d67-81e8-944c7eeb1f92 · outbound

This paper cites Towards robust interpretability with self-explaining neural networks,.

Multi-criteria Rank-based Aggregation for Explainable AI Towards robust interpretability with self-explaining neural networks,

Reference 12

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Observation 2cd0034e-2fee-4c85-bd20-94cb0047fa64 · outbound

This paper cites Global Aggregations of Local Explanations for Black Box models.

Multi-criteria Rank-based Aggregation for Explainable AI Global Aggregations of Local Explanations for Black Box models

Reference 13

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Observation b38be770-6b54-46e5-b75d-deca800f16d9 · outbound

This paper cites Evaluating and Aggregating Feature-based Model Explanations.

Multi-criteria Rank-based Aggregation for Explainable AI Evaluating and Aggregating Feature-based Model Explanations

Reference 14

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This paper cites Methods for multiple attribute decision making,.

Multi-criteria Rank-based Aggregation for Explainable AI Methods for multiple attribute decision making,

Reference 15

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Observation ccf079dc-077a-4d2b-b971-4c49feb16033 · outbound

This paper cites Multi- criteria inventory classification using a new method of evaluation based on distance from average solution (edas),.

Multi-criteria Rank-based Aggregation for Explainable AI Multi- criteria inventory classification using a new method of evaluation based on distance from average solution (edas),

Reference 16

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This paper cites Data fusion with estimated weights,.

Multi-criteria Rank-based Aggregation for Explainable AI Data fusion with estimated weights,

Reference 17

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This paper cites Condorcet fusion for improved re- trieval,.

Multi-criteria Rank-based Aggregation for Explainable AI Condorcet fusion for improved re- trieval,

Reference 18

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Observation 796a8a6c-0e37-4f44-97b8-f797c960c217 · outbound

This paper cites Models for metasearch,.

Multi-criteria Rank-based Aggregation for Explainable AI Models for metasearch,

Reference 19

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Observation 9ea9d42c-600b-457a-b97e-37f88b73482e · outbound

This paper cites Transparency, auditability, and explainability of machine learning models in credit scoring,.

Multi-criteria Rank-based Aggregation for Explainable AI Transparency, auditability, and explainability of machine learning models in credit scoring,

Reference 20

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Observation c3379156-2a0e-4c09-8057-b27d53b37157 · outbound

This paper cites Explainable ai for credit assessment in banks,.

Multi-criteria Rank-based Aggregation for Explainable AI Explainable ai for credit assessment in banks,

Reference 21

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Observation 0de7c648-568e-481c-ab2b-ebd29fbfd057 · outbound

This paper cites Glocalx - from local to global explanations of black box ai models,.

Multi-criteria Rank-based Aggregation for Explainable AI Glocalx - from local to global explanations of black box ai models,

Reference 22

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Observation dded81d4-dffe-4dfb-a18a-d0498313d41a · outbound

This paper cites Axiomatic aggregations of abductive explanations,.

Multi-criteria Rank-based Aggregation for Explainable AI Axiomatic aggregations of abductive explanations,

Reference 23

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Observation 008cb57c-a7a1-4e97-810d-7a60e8a0be96 · outbound

This paper cites Vice: Visual counterfac- tual explanations for machine learning models,.

Multi-criteria Rank-based Aggregation for Explainable AI Vice: Visual counterfac- tual explanations for machine learning models,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:12.329897Z

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Observation 78156421-5eac-4b2b-a101-b911aff5cfb5 · outbound

This paper cites Evaluation metrics for xai: A review, taxonomy, and practical applications,.

Multi-criteria Rank-based Aggregation for Explainable AI Evaluation metrics for xai: A review, taxonomy, and practical applications,

Reference 25

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This paper cites Gradient-based attribution methods,.

Multi-criteria Rank-based Aggregation for Explainable AI Gradient-based attribution methods,

Reference 26

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Observation 85ebff9c-ff6c-43f5-9aa4-6c4ae2f32702 · outbound

This paper cites Minimal model explanations,.

Multi-criteria Rank-based Aggregation for Explainable AI Minimal model explanations,

Reference 27

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Observation 87b0fdf7-a227-4e76-84b6-e83492fefe8c · outbound

This paper cites Inference to the best explanation,.

Multi-criteria Rank-based Aggregation for Explainable AI Inference to the best explanation,

Reference 28

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Observation 2ec3cf60-5e31-4f85-9079-cbe063792a97 · outbound

This paper cites Can I Trust the Explainer? Verifying Post-hoc Explanatory Methods.

Multi-criteria Rank-based Aggregation for Explainable AI Can I Trust the Explainer? Verifying Post-hoc Explanatory Methods

Reference 29

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This paper cites Agree: a feature attribution aggregation framework to address explainer dis- agreements with alignment metrics,.

Multi-criteria Rank-based Aggregation for Explainable AI Agree: a feature attribution aggregation framework to address explainer dis- agreements with alignment metrics,

Reference 30

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Observation 72aab1e3-a54f-439b-ae39-c4d74ec2edd3 · outbound

This paper cites Accelerating the global aggre- gation of local explanations,.

Multi-criteria Rank-based Aggregation for Explainable AI Accelerating the global aggre- gation of local explanations,

Reference 31

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Observation 32d4d1fe-dda6-41eb-9c62-0e6a26f2bd43 · outbound

This paper cites Provably better explanations with optimized aggregation of feature attributions,.

Multi-criteria Rank-based Aggregation for Explainable AI Provably better explanations with optimized aggregation of feature attributions,

Reference 32

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Observation 4ff40443-905b-4997-bb7b-c665964d4d5b · outbound

This paper cites T-Explainer: A Model-Agnostic Explainability Framework Based on Gradients.

Multi-criteria Rank-based Aggregation for Explainable AI T-Explainer: A Model-Agnostic Explainability Framework Based on Gradients

Reference 33

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Observation bb8e0882-e5ae-4e03-9621-abba7f642260 · outbound

This paper cites Making deep learning-based predictions for credit scoring explainable,.

Multi-criteria Rank-based Aggregation for Explainable AI Making deep learning-based predictions for credit scoring explainable,

Reference 34

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This paper cites A comparative analysis of lime and shap interpreters with explainable ml- based diabetes predictions,.

Multi-criteria Rank-based Aggregation for Explainable AI A comparative analysis of lime and shap interpreters with explainable ml- based diabetes predictions,

Reference 35

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Observation 90a64e87-6ad7-4f3c-b3d8-1b2c30b56725 · outbound

This paper cites Why should i trust you? explaining the predictions of any classifier,.

Multi-criteria Rank-based Aggregation for Explainable AI Why should i trust you? explaining the predictions of any classifier,

Reference 36

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Observation 792196cc-d189-43cb-a30c-8bbf7acd8c3e · outbound

This paper cites A unified approach to interpreting model predictions,.

Multi-criteria Rank-based Aggregation for Explainable AI A unified approach to interpreting model predictions,

Reference 37

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Observation 93fa6315-c660-4fad-b382-0e3cc5c9b9df · outbound

This paper cites Anchors: High-precision model-agnostic explanations,.

Multi-criteria Rank-based Aggregation for Explainable AI Anchors: High-precision model-agnostic explanations,

Reference 38

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This paper cites The new method of multi-criteria complex pro-portional assessment of projects.),.

Multi-criteria Rank-based Aggregation for Explainable AI The new method of multi-criteria complex pro-portional assessment of projects.),

Reference 39

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Observation 6c2fdddd-d096-4256-bc73-0701fb294550 · outbound

This paper cites The promethee methods for mcdm; the promcalc, gaia and bankadviser software,.

Multi-criteria Rank-based Aggregation for Explainable AI The promethee methods for mcdm; the promcalc, gaia and bankadviser software,

Reference 40

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Observation 1babe03d-3e29-4ca6-ab0c-f08c21743602 · outbound

This paper cites Note—a preference ranking organisation method (the promethee method for multiple criteria decision-making),.

Multi-criteria Rank-based Aggregation for Explainable AI Note—a preference ranking organisation method (the promethee method for multiple criteria decision-making),

Reference 41

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Observation c730365e-948d-4605-b1f9-c38a5bc020dd · outbound

This paper cites A new additive ratio assessment (aras) method in multicriteria decision-making,.

Multi-criteria Rank-based Aggregation for Explainable AI A new additive ratio assessment (aras) method in multicriteria decision-making,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:10.818102Z

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Observation 862c11f1-ea54-4da3-83bc-f544a800f97f · outbound

This paper cites A combined compromise solution (cocoso) method for multi-criteria decision-making problems,.

Multi-criteria Rank-based Aggregation for Explainable AI A combined compromise solution (cocoso) method for multi-criteria decision-making problems,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:10.741665Z

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Observation d1a3f0d2-9f6e-403c-a6b9-3db3fe6ea7be · outbound

This paper cites A new combinative distance-based assessment (codas) method for multi-criteria decision-making,.

Multi-criteria Rank-based Aggregation for Explainable AI A new combinative distance-based assessment (codas) method for multi-criteria decision-making,

Reference 44

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Observation 8622b0e0-2ab4-4d7f-9997-3ff9580d379e · outbound

This paper cites The selection of transport and handling re- sources in logistics centers using multi-attributive border approximation area comparison (mabac),.

Multi-criteria Rank-based Aggregation for Explainable AI The selection of transport and handling re- sources in logistics centers using multi-attributive border approximation area comparison (mabac),

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:10.497663Z

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Observation d77b0133-1ae8-49c1-b0b0-e6cadd5ecd2f · outbound

This paper cites A com- prehensive study on fidelity metrics for xai,.

Multi-criteria Rank-based Aggregation for Explainable AI A com- prehensive study on fidelity metrics for xai,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:10.424119Z

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Observation 961ebb9f-546b-439a-8903-60470febb147 · outbound

This paper cites Breast cancer wisconsin (diagnostic),.

Multi-criteria Rank-based Aggregation for Explainable AI Breast cancer wisconsin (diagnostic),

Reference 47

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This paper cites Student depression project,.

Multi-criteria Rank-based Aggregation for Explainable AI Student depression project,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:10.257241Z

Source-reported events for the cited work

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Observation 726b84fa-3262-48b4-bff3-60971c2b4347 · outbound

This paper cites Statlog (German Credit Data),.

Multi-criteria Rank-based Aggregation for Explainable AI Statlog (German Credit Data),

Reference 49

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Observation c2c42e9b-1b3d-4e7c-8514-1af4de81ce5d · outbound

This paper cites default of credit card clients,.

Multi-criteria Rank-based Aggregation for Explainable AI default of credit card clients,

Reference 50

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Observation 36d48b92-6cad-4f81-9bde-24db206897bb · outbound

This paper cites Pakdd 2010 data mining com- petition: Re-calibration of a credit risk assessment system based on biased data,.

Multi-criteria Rank-based Aggregation for Explainable AI Pakdd 2010 data mining com- petition: Re-calibration of a credit risk assessment system based on biased data,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:10.147555Z

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