conftrace_

model explanation

155 papers

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Co-occurring keywords

feature attribution (280) model interpretability (519) shapley value (206) feature importance (139) explainable ai (480) black-box model (90) text classification (6793) graph neural network (3962) attention mechanism (4001) neural network (6616)

Papers

RegExplainer: Generating Explanations for Graph Neural Networks in Regression Tasks NIPS 2024
LLM Explainability via Attributive Masking Learning EMNLP 2024
DecompX: Explaining Transformers Decisions by Propagating Token Decomposition ACL 2023
Dividing and Conquering a BlackBox to a Mixture of Interpretable Models: Route, Interpret, Repeat ICML 2023
Explainability as statistical inference ICML 2023
Incorporating Attribution Importance for Improving Faithfulness Metrics ACL 2023
But Are You Sure? An Uncertainty-Aware Perspective on Explainable AI AISTATS 2023
SAME: Uncovering GNN Black Box with Structure-aware Shapley-based Multipiece Explanations NIPS 2023
Rethinking Explaining Graph Neural Networks via Non-parametric Subgraph Matching ICML 2023
Causal Proxy Models for Concept-based Model Explanations ICML 2023
An Integrated Approach for Political Bias Prediction and Explanation Based on Discursive Structure ACL 2023
Bridging the Gap Between Model Explanations in Partially Annotated Multi-Label Classification CVPR 2023
Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application to Credit-Risk Evaluation JMLR 2023
Explaining Image Classifiers With Multiscale Directional Image Representation CVPR 2023
LEXPLAIN: Improving Model Explanations via Lexicon Supervision ACL 2023
Unifying local and global model explanations by functional decomposition of low dimensional structures AISTATS 2023
Counterfactuals of Counterfactuals: a back-translation-inspired approach to analyse counterfactual editors ACL 2023
Overlooked Factors in Concept-Based Explanations: Dataset Choice, Concept Learnability, and Human Capability CVPR 2023
Explanation Regeneration via Information Bottleneck ACL 2023
Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations and Beyond JMLR 2023
“Honey, Tell Me What’s Wrong”, Global Explanation of Textual Discriminative Models through Cooperative Generation EMNLP 2023
XRand: Differentially Private Defense against Explanation-Guided Attacks AAAI 2023
Manifold Restricted Interventional Shapley Values AISTATS 2023
Towards Better Explanations for Object Detection ACML 2023
FunnyBirds: A Synthetic Vision Dataset for a Part-Based Analysis of Explainable AI Methods ICCV 2023