The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations | Paper Citation Record

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations OpenXAI: Towards a Transparent Evaluation of Model Explanations

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This paper cites Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI.

The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations The Disagreement Problem in Faithfulness Metrics

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This paper cites Do We Need Another Explainable AI Method? Toward Unifying Post-hoc XAI Evaluation Methods into an Interactive and Multi-dimensional Benchmark.

The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Do We Need Another Explainable AI Method? Toward Unifying Post-hoc XAI Evaluation Methods into an Interactive and Multi-dimensional Benchmark

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This paper cites An Introduction to Vision-Language Modeling.

The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations An Introduction to Vision-Language Modeling

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations A Survey on the Explainability of Supervised Machine Learning

Reference 12

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This paper cites Carvalho, Eduardo M.

The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Carvalho, Eduardo M

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations REX: Reasoning-aware and Grounded Explanation

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This paper cites Explainable Reinforcement Learning for Broad-XAI: A Conceptual Framework and Survey.

The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Explainable Reinforcement Learning for Broad-XAI: A Conceptual Framework and Survey

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations What Does Explainable AI Really Mean? A New Conceptualization of Perspectives

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Towards A Rigorous Science of Interpretable Machine Learning

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Vera Liao, Michael Muller, Mark O

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Peeking Inside the Black Box: Visualizing Statistical Learning with Plots of Individual Conditional Expectation

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Right to Explanation

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Interpretable Credit Application Predictions With Counterfactual Explanations

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Out-of-Distribution Generalization via Risk Extrapolation (REx)

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations What Do We Want From Explainable Artificial Intelligence (XAI)? -- A Stakeholder Perspective on XAI and a Conceptual Model Guiding Interdisciplinary XAI Research

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Achievements and Challenges in Explaining Deep Learning based Computer-Aided Diagnosis Systems

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations A Unified Approach to Interpreting Model Predictions

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations A Survey on Bias and Fairness in Machine Learning

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Explanation in Human-AI Systems: A Literature Meta-Review, Synopsis of Key Ideas and Publications, and Bibliography for Explainable AI

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations James Murdoch, Chandan Singh, Karl Kumbier, Reza Abbasi-Asl, and Bin Yu

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Osoba and William Welser IV

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Multimodal Explanations: Justifying Decisions and Pointing to the Evidence

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This paper cites an unresolved cited work.

The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Unresolved cited work

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Reference 62

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Learning Transferable Visual Models From Natural Language Supervision

Reference 63

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This paper cites Explanation Methods in Deep Learning: Users, Values, Concerns and Challenges.

The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Explanation Methods in Deep Learning: Users, Values, Concerns and Challenges

Reference 64

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Explainable Deep Learning: A Field Guide for the Uninitiated

Reference 65

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Reference 66

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Why Should I Trust You?

Reference 67

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Unresolved cited work

Reference 68

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Explainable Artificial Intelligence (XAI) on TimeSeries Data: A Survey

Reference 69

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This paper cites Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead.

The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead

Reference 70

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Unresolved cited work

Reference 71

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Unresolved cited work

Reference 72

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models

Reference 73

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Risk Assessment for Machine Learning Models

Reference 74

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Observation 9ebbcc48-5800-4442-b2d7-473a4e14dc2f · outbound

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Weld, and Leah Findlater

Reference 75

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Intriguing properties of neural networks

Reference 76

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Unresolved cited work

Reference 77

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Observation c712d2d8-4bf5-4977-a30b-9167e1a254ba · outbound

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Bissyandé, and Jacques Klein

Reference 78

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Observation d70b30ea-4872-4824-b4ea-8ee154ec997c · outbound

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Unresolved cited work

Reference 79

Resolution: verified exact; doi, observed 2026-08-10T21:26:52.810432Z

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Observation 99868417-3763-45a3-a9e9-137ad4521638 · outbound

This paper cites Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR.

The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR

Reference 80

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Unresolved cited work

Reference 81

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The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Explainability for Large Language Models: A Survey

Reference 82

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This paper cites an unresolved cited work.

The State of Post-Hoc Local XAI Techniques for Image Processing: Challenges and Motivations Unresolved cited work

Reference 83

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