interpretable machine learning

139 papers

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Also known as

XAI IML

Co-occurring keywords

interpretable model (158) decision tree (322) concept bottleneck model (41) neural network (6616) explainable ai (478) model interpretability (510) image classification (1943) concept bottleneck (29) text classification (6776) model explanation (154)

Papers

To make someone do something: mining alert-style directives in Bulgarian social media for low-resource language modelling EACL 2026

Interpretable Machine Learning for In-Home Mild Cognitive Impairment Detection AAAI 2026

Disentangled Table-Graph Representation for Interpretable Transmission Line Fault Location AAAI 2025

Creating Coherence in Federated Non-Negative Matrix Factorization AAAI 2025

BoolXAI: Explainable AI Using Expressive Boolean Formulas AAAI 2025

A Bit of This, a Bit of That: Building a Genre and Topic Annotated Dataset of Historical Newspaper Articles with Soft Labels and Confidence Scores NAACL 2025

Interpretable DNFs IJCAI 2025

IRIS: Interpretable Retrieval-Augmented Classification for Long Interspersed Document Sequences ACL 2025

Language Guided Concept Bottleneck Models for Interpretable Continual Learning CVPR 2025

Rashomon Sets for Prototypical-Part Networks: Editing Interpretable Models in Real-Time CVPR 2025

How Your Location Relates to Health: Variable Importance and Interpretable Machine Learning for Environmental and Sociodemographic Data AAAI 2025

Intervening in Black Box: Concept Bottleneck Model for Enhancing Human Neural Network Mutual Understanding ICCV 2025

GeoPro-Net: Learning Interpretable Spatiotemporal Prediction Models Through Statistically-Guided Geo-Prototyping AAAI 2025

AutoCT: Automating Interpretable Clinical Trial Prediction with LLM Agents EMNLP 2025

Learning Optimal Oblique Decision Trees with (Max)SAT IJCAI 2025

Counterfactual Explanations for Continuous Action Reinforcement Learning IJCAI 2025

ClinStructor: AI-Powered Structuring of Unstructured Clinical Texts IJCNLP 2025

MatchXplain: Analyzing Preferences, Explaining Outcomes, and Simplifying Decisions IJCAI 2025

SUB: Benchmarking CBM Generalization via Synthetic Attribute Substitutions ICCV 2025

Beyond Concept Bottleneck Models: How to Make Black Boxes Intervenable? NIPS 2024

Driving Through the Concept Gridlock: Unraveling Explainability Bottlenecks in Automated Driving WACV 2024

Evaluating Pre-trial Programs Using Interpretable Machine Learning Matching Algorithms for Causal Inference AAAI 2024

Relevant Irrelevance: Generating Alterfactual Explanations for Image Classifiers IJCAI 2024

Inductive Knowledge Graph Completion with GNNs and Rules: An Analysis COLING 2024

Stochastic Concept Bottleneck Models NIPS 2024