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Faithful and Customizable Explanations of Black Box Models
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Outgoing claims: the papers this work cites, builds on, or argues with.
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What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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A Functionally-Grounded Benchmark Framework for XAI Methods: Insights and Foundations from a Systematic Literature Review
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Improving Human Verification of LLM Reasoning through Interactive Explanation Interfaces
inferred← citeshttps://doi.org/10.11606/d.100.2023.tde-22052023-205242openalex-snapshot
Uso de agrupamento para alcançar explicabilidade global de modelos de aprendizado de máquina
inferred← citeshttps://doi.org/10.1177/00187208261443764openalex-snapshot
Efficiency Pitfalls of Explainable AI in Clinical Diagnostic and Treatment Human-AI Workflows
inferred← citeshttps://doi.org/10.1177/14614448251339493openalex-snapshot
Exploring social media users’ experiences with algorithmic transparency cues
inferred← citeshttps://doi.org/10.1177/21582440251380135openalex-snapshot
Trust Under Bounded Rationality: Exploring Human-AI Interaction in Decision-Making Through Large Language Models
inferred← citeshttps://doi.org/10.1259/bjr.20230142openalex-snapshot
Interpretable artificial intelligence in radiology and radiation oncology
inferred← citeshttps://doi.org/10.1287/mnsc.2023.4819openalex-snapshot
Treatment Effect Risk: Bounds and Inference
inferred← citeshttps://doi.org/10.1371/journal.pone.0282595openalex-snapshot
Fast and accurate interpretation of workload classification model
inferred← citeshttps://doi.org/10.14763/2021.2.1564openalex-snapshot
Black box algorithms and the rights of individuals: no easy solution to the “explainability” problem
inferred← citeshttps://doi.org/10.1515/icom-2020-0024openalex-snapshot
Explainable AI and Multi-Modal Causability in Medicine
inferred← citeshttps://doi.org/10.1609/aaai.v34i09.7077openalex-snapshot
AI for Explaining Decisions in Multi-Agent Environments
inferred← citeshttps://doi.org/10.1609/aaai.v35i9.16925openalex-snapshot
Justicia: A Stochastic SAT Approach to Formally Verify Fairness
inferred← citeshttps://doi.org/10.1609/aaai.v35i9.16963openalex-snapshot
Accurate and Robust Feature Importance Estimation under Distribution Shifts
inferred← citeshttps://doi.org/10.1609/aaai.v36i5.20507openalex-snapshot
Sufficient Reasons for Classifier Decisions in the Presence of Domain Constraints
inferred← citeshttps://doi.org/10.1609/aaai.v36i8.20805openalex-snapshot
Constraint-Driven Explanations for Black-Box ML Models
inferred← citeshttps://doi.org/10.1609/hcomp.v10i1.21997openalex-snapshot
A Human-Centric Perspective on Model Monitoring
inferred← citeshttps://doi.org/10.1609/icwsm.v14i1.7282openalex-snapshot
Feature-Based Explanations Don't Help People Detect Misclassifications of Online Toxicity
inferred← citeshttps://doi.org/10.1613/jair.1.12228openalex-snapshot
A Survey on the Explainability of Supervised Machine Learning
inferred← citeshttps://doi.org/10.1613/jair.1.13482openalex-snapshot
Efficient Learning of Interpretable Classification Rules
inferred← citeshttps://doi.org/10.18653/v1/2020.acl-main.386openalex-snapshot
Towards Faithfully Interpretable NLP Systems: How Should We Define and Evaluate Faithfulness?
inferred← citeshttps://doi.org/10.18653/v1/2021.acl-long.88openalex-snapshot
Explainable Prediction of Text Complexity: The Missing Preliminaries for Text Simplification
inferred← citeshttps://doi.org/10.18653/v1/2021.naacl-main.245openalex-snapshot
Faithfully Explainable Recommendation via Neural Logic Reasoning
inferred← citeshttps://doi.org/10.18653/v1/2022.naacl-main.392openalex-snapshot
ExSum: From Local Explanations to Model Understanding
inferred← citeshttps://doi.org/10.18653/v1/2023.emnlp-main.832openalex-snapshot
MaNtLE: Model-agnostic Natural Language Explainer
inferred← citeshttps://doi.org/10.18699/vjgb-25-49openalex-snapshot
Genomic prediction of plant traits by popular machine learning methods
inferred← citeshttps://doi.org/10.21202/jdtl.2023.13openalex-snapshot
Legal Aspects of the Use Artificial Intelligence in Telemedicine
inferred← citeshttps://doi.org/10.21203/rs.3.rs-2963888/v1openalex-snapshot
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective
inferred← citeshttps://doi.org/10.21203/rs.3.rs-448572/v1openalex-snapshot
Interpretable Machine Learning for Genomics
inferred← citeshttps://doi.org/10.2139/ssrn.5964045openalex-snapshot
Explainable AI: XVARS Outperforms SHAP in Terms of Computational Speed and Sampling Robustness
inferred← citeshttps://doi.org/10.2196/42047openalex-snapshot
An Explainable Artificial Intelligence Software Tool for Weight Management Experts (PRIMO): Mixed Methods Study
inferred← citeshttps://doi.org/10.22541/au.163284810.09140868/v1openalex-snapshot
Qualitative investigation in explainable artificial intelligence: A bit more insight from social science
inferred← citeshttps://doi.org/10.22541/essoar.171052510.02996233/v1openalex-snapshot
On Robustness of the Explanatory Power of Machine Learning Models
inferred← citeshttps://doi.org/10.24834/isbn.9789178771875openalex-snapshot
Human In Command Machine Learning
inferred← citeshttps://doi.org/10.25740/ry909yd9970openalex-snapshot
Unpacking the Black Box: Regulating Algorithmic Decisions
inferred← citeshttps://doi.org/10.31234/osf.io/4nvtsopenalex-snapshot
Learning Representations by Humans, for Humans
inferred← citeshttps://doi.org/10.3233/faia230423openalex-snapshot
Neural Architecture Search for Explainable Networks
inferred← citeshttps://doi.org/10.32657/10356/164493openalex-snapshot
From medical imaging to explainable artificial intelligence
inferred← citeshttps://doi.org/10.3389/frai.2023.1099407openalex-snapshot
Achieving descriptive accuracy in explanations via argumentation: The case of probabilistic classifiers
inferred← citeshttps://doi.org/10.3390/a19090768openalex-snapshot
Domain-Informed Explainable AI for Suction Prediction in Xanthan Gum-Treated Clays
inferred← citeshttps://doi.org/10.3390/ai4030033openalex-snapshot
Explainable Image Classification: The Journey So Far and the Road Ahead
inferred← citeshttps://doi.org/10.3390/ai7030114openalex-snapshot
Trust Triangle: A Reliability-Validity-Generation Framework for Explainable Credit Card Fraud Detection with RAG-Enhanced LLMs Reasoning
inferred← citeshttps://doi.org/10.3390/info13100464openalex-snapshot
Constructing Explainable Classifiers from the Start—Enabling Human-in-the Loop Machine Learning
inferred← citeshttps://doi.org/10.3390/info15010004openalex-snapshot
Explainable AI Evaluation: A Top-Down Approach for Selecting Optimal Explanations for Black Box Models
inferred← citeshttps://doi.org/10.3390/jcp2010011openalex-snapshot
Association Rule Mining Meets Regression Analysis: An Automated Approach to Unveil Systematic Biases in Decision-Making Processes
inferred← citeshttps://doi.org/10.3390/make5040086openalex-snapshot
Explainable Artificial Intelligence Using Expressive Boolean Formulas
inferred← citeshttps://doi.org/10.3390/s24010288openalex-snapshot
Evaluation of Malware Classification Models for Heterogeneous Data
inferred← citeshttps://doi.org/10.3390/sym13122439openalex-snapshot
A Review of Interpretable ML in Healthcare: Taxonomy, Applications, Challenges, and Future Directions
inferred← citeshttps://doi.org/10.34190/eciair.4.1.851openalex-snapshot
Suggestions for a Revision of the European Smart Robot Liability Regime
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