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

Libra-CAM: An Activation-Based Attribution Based on the Linear Approximation of Deep Neural Nets and Threshold Calibration IJCAI 2022
Anomaly Explanation IJCAI 2022
AttExplainer: Explain Transformer via Attention by Reinforcement Learning IJCAI 2022
Explain, Edit, and Understand: Rethinking User Study Design for Evaluating Model Explanations AAAI 2022
Trading Complexity for Sparsity in Random Forest Explanations AAAI 2022
Constraint-Driven Explanations for Black-Box ML Models AAAI 2022
Manipulating SHAP via Adversarial Data Perturbations (Student Abstract) AAAI 2022
FOCUS: Flexible Optimizable Counterfactual Explanations for Tree Ensembles AAAI 2022
A Comparative Study of Faithfulness Metrics for Model Interpretability Methods ACL 2022
Consistent Explanations by Contrastive Learning CVPR 2022
Washing The Unwashable : On The (Im)possibility of Fairwashing Detection NIPS 2022
Learning to Generate Inversion-Resistant Model Explanations NIPS 2022
Unsupervised Causal Binary Concepts Discovery with VAE for Black-Box Model Explanation AAAI 2022
NoiseGrad — Enhancing Explanations by Introducing Stochasticity to Model Weights AAAI 2022
Supervising Model Attention with Human Explanations for Robust Natural Language Inference AAAI 2022
Reinforcement Learning Explainability via Model Transforms (Student Abstract) AAAI 2022
Can Explanations Be Useful for Calibrating Black Box Models? ACL 2022
How (Un)Faithful is Attention? EMNLP 2022
Human Ratings Do Not Reflect Downstream Utility: A Study of Free-Text Explanations for Model Predictions EMNLP 2022
Task-Agnostic Graph Explanations NIPS 2022
Explaining Preferences with Shapley Values NIPS 2022
DALE: Differential Accumulated Local Effects for efficient and accurate global explanations ACML 2022
Alibi Explain: Algorithms for Explaining Machine Learning Models JMLR 2021
An Analysis of LIME for Text Data AISTATS 2021
Explaining by Removing: A Unified Framework for Model Explanation JMLR 2021