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Interpretability

349 directly classified papers

Papers per year

Papers

Accurate Estimation of Feature Importance Faithfulness for Tree Models AAAI 2025
Faithful and Accurate Self-Attention Attribution for Message Passing Neural Networks via the Computation Tree Viewpoint AAAI 2025
Unlocking Better Closed-Set Alignment Based on Neural Collapse for Open-Set Recognition AAAI 2025
A Robust Prototype-Based Network with Interpretable RBF Classifier Foundations AAAI 2025
ReX: A Framework for Incorporating Temporal Information in Model-Agnostic Local Explanation Techniques AAAI 2025
Prompt-CAM: Making Vision Transformers Interpretable for Fine-Grained Analysis CVPR 2025
Probabilistic Explanations for Linear Models AAAI 2025
Functional Connectomes of Neural Networks AAAI 2025
AutoSciLab: A Self-Driving Laboratory for Interpretable Scientific Discovery AAAI 2025
Beyond Accuracy: On the Effects of Fine-Tuning Towards Vision-Language Model’s Prediction Rationality AAAI 2025
InteDisUX: Intepretation-Guided Discriminative User-Centric Explanation for Time Series AAAI 2025
ProtoVQA: An Adaptable Prototypical Framework for Explainable Fine-Grained Visual Question Answering EMNLP 2025
Interpretable Failure Detection with Human-Level Concepts AAAI 2025
IRT-Router: Effective and Interpretable Multi-LLM Routing via Item Response Theory ACL 2025
Beyond Prompt Engineering: Robust Behavior Control in LLMs via Steering Target Atoms ACL 2025
ProtoLens: Advancing Prototype Learning for Fine-Grained Interpretability in Text Classification ACL 2025
Discovering Biases in Information Retrieval Models Using Relevance Thesaurus as Global Explanation EMNLP 2024
Generating Diagnostic and Actionable Explanations for Fair Graph Neural Networks AAAI 2024
Evaluating Pre-trial Programs Using Interpretable Machine Learning Matching Algorithms for Causal Inference AAAI 2024
MICA: Towards Explainable Skin Lesion Diagnosis via Multi-Level Image-Concept Alignment AAAI 2024
Selective Explanations NIPS 2024
G–LIME: Statistical Learning for Local Interpretations of Deep Neural Networks Using Global Priors (Abstract Reprint) AAAI 2024
Interactive Mars Image Content-Based Search with Interpretable Machine Learning AAAI 2024
Empowering CAM-Based Methods with Capability to Generate Fine-Grained and High-Faithfulness Explanations AAAI 2024
Stochastic Concept Bottleneck Models NIPS 2024