conftrace_

feature importance

139 papers

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Also known as

FI

Co-occurring keywords

model interpretability (519) model explanation (155) explainable ai (480) shapley value (206) neural network (6616) feature attribution (280) text classification (6793) model interpretation (93) explainable artificial intelligence (130) random forest (326)

Papers

BlockBoost: Scalable and Efficient Blocking through Boosting AISTATS 2024
The Key Points: Using Feature Importance to Identify Shortcomings in Sign Language Recognition Models COLING 2024
An Information-Theoretic Approach to Analyze NLP Classification Tasks ACL 2024
Testing Semantic Importance via Betting NIPS 2024
Permutation-Based Hypothesis Testing for Neural Networks AAAI 2024
Using Machine Learning to Predict Item Difficulty and Response Time in Medical Tests NAACL 2024
Relevant Irrelevance: Generating Alterfactual Explanations for Image Classifiers IJCAI 2024
Discretionary Trees: Understanding Street-Level Bureaucracy via Machine Learning AAAI 2024
Information-theoretic hypothesis generation of relative cue weighting for the voicing contrast INTERSPEECH 2024
Learning Performance Maximizing Ensembles with Explainability Guarantees AAAI 2024
Efficient SAGE Estimation via Causal Structure Learning AISTATS 2023
Enhancing textual counterfactual explanation intelligibility through Counterfactual Feature Importance ACL 2023
A Statistical Exploration of Text Partition Into Constituents: The Case of the Priestly Source in the Books of Genesis and Exodus ACL 2023
Saliency Map Verbalization: Comparing Feature Importance Representations from Model-free and Instruction-based Methods ACL 2023
Theoretical Behavior of XAI Methods in the Presence of Suppressor Variables ICML 2023
Sample based Explanations via Generalized Representers NIPS 2023
Utility-Preserving Privacy-Enabled Speech Embeddings for Emotion Detection INTERSPEECH 2023
Symbolic Metamodels for Interpreting Black-Boxes Using Primitive Functions AAAI 2023
XRand: Differentially Private Defense against Explanation-Guided Attacks AAAI 2023
Identifiable Contrastive Learning with Automatic Feature Importance Discovery NIPS 2023
Unifying local and global model explanations by functional decomposition of low dimensional structures AISTATS 2023
Ultra-marginal Feature Importance: Learning from Data with Causal Guarantees AISTATS 2023
Explainability as statistical inference ICML 2023
Attribution-based Explanations that Provide Recourse Cannot be Robust JMLR 2023
Figurative Language Processing: A Linguistically Informed Feature Analysis of the Behavior of Language Models and Humans ACL 2023