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

From Decision Trees to Boolean Logic: A Fast and Unified SHAP Algorithm AAAI 2026
Parallel Universes, Parallel Languages: A Comprehensive Study on LLM-based Multilingual Counterfactual Example Generation ACL 2026
Strengths and Limitations of Word-Based Task Explainability in Vision Language Models: a Case Study on Biological Sex Biases in the Medical Domain ACL 2025
Unlocking the Game: Estimating Games in Möbius Representation for Explanation and High-Order Interaction Detection AAAI 2025
Assessing the Reliability of LLMs Annotations in the Context of Demographic Bias and Model Explanation ACL 2025
Fast Explanations via Policy Gradient-Optimized Explainer IJCAI 2025
LLMs Don’t Know Their Own Decision Boundaries: The Unreliability of Self-Generated Counterfactual Explanations EMNLP 2025
When Backdoors Speak: Understanding LLM Backdoor Attacks Through Model-Generated Explanations ACL 2025
InteDisUX: Intepretation-Guided Discriminative User-Centric Explanation for Time Series AAAI 2025
Support Vector-based Estimation of Multilinear Games for Feature Selection and Explanation AAAI 2025
Selective Explanations NIPS 2024
Temporal Logic Explanations for Dynamic Decision Systems Using Anchors and Monte Carlo Tree Search (Abstract Reprint) AAAI 2024
G–LIME: Statistical Learning for Local Interpretations of Deep Neural Networks Using Global Priors (Abstract Reprint) AAAI 2024
Causal Analysis for Robust Interpretability of Neural Networks WACV 2024
Identifying Important Group of Pixels using Interactions CVPR 2024
Self-Interpretable Graph Learning with Sufficient and Necessary Explanations AAAI 2024
What Sketch Explainability Really Means for Downstream Tasks? CVPR 2024
Learning Performance Maximizing Ensembles with Explainability Guarantees AAAI 2024
Pathwise Explanation of ReLU Neural Networks AISTATS 2024
Stochastic Amortization: A Unified Approach to Accelerate Feature and Data Attribution NIPS 2024
XAL: EXplainable Active Learning Makes Classifiers Better Low-resource Learners NAACL 2024
Fostering Trustworthiness in Machine Learning Algorithms AAAI 2024
RegExplainer: Generating Explanations for Graph Neural Networks in Regression Tasks NIPS 2024
Digital Socrates: Evaluating LLMs through Explanation Critiques ACL 2024
From Language Modeling to Instruction Following: Understanding the Behavior Shift in LLMs after Instruction Tuning NAACL 2024