Interpretability

Exploring and Mitigating Shortcut Learning for Generative Large Language Models COLING 2024 Exploring Context Window of Large Language Models via Decomposed Positional Vectors NeurIPS 2024 Exploring Effective Stimulus Encoding via Vision System Modeling for Visual Prostheses ICLR 2024 Exploring Interpretability of Independent Components of Word Embeddings with Automated Word Intruder Test COLING 2024 Exploring Intrinsic Dimension for Vision-Language Model Pruning ICML 2024 Exploring Spatial Schema Intuitions in Large Language and Vision Models ACL 2024 Exploring the Jungle of Bias: Political Bias Attribution in Language Models via Dependency Analysis EMNLP 2024 Exploring the LLM Journey from Cognition to Expression with Linear Representations ICML 2024 Exploring the Low-Pass Filtering Behavior in Image Super-Resolution ICML 2024 Exploring the Relationship Between Intrinsic Stigma in Masked Language Models and Training Data Using the Stereotype Content Model COLING 2024 Exploring the trade-off between deep-learning and explainable models for brain-machine interfaces NeurIPS 2024 Exploring the Trade-off Between Model Performance and Explanation Plausibility of Text Classifiers Using Human Rationales NAACL 2024 Exponent Relaxation of Polynomial Zonotopes and Its Applications in Formal Neural Network Verification AAAI 2024 Exposing propaganda: an analysis of stylistic cues comparing human annotations and machine classification EACL 2024 Exposing the Deception: Uncovering More Forgery Clues for Deepfake Detection AAAI 2024 Extracting Lexical Features from Dialects via Interpretable Dialect Classifiers NAACL 2024 FAC2E: Better Understanding Large Language Model Capabilities by Dissociating Language and Cognition EMNLP 2024 Facial Identity Anonymization via Intrinsic and Extrinsic Attention Distraction CVPR 2024 Fact-and-Reflection (FaR) Improves Confidence Calibration of Large Language Models ACL 2024 Fact-Checking the Output of Large Language Models via Token-Level Uncertainty Quantification ACL 2024 Factorized Explainer for Graph Neural Networks AAAI 2024 Factual Confidence of LLMs: on Reliability and Robustness of Current Estimators ACL 2024 Fair Multivariate Adaptive Regression Splines for Ensuring Equity and Transparency AAAI 2024 Fair Representation Learning with Maximum Mean Discrepancy Distance Constraint (Student Abstract) AAAI 2024 Faithful and Efficient Explanations for Neural Networks via Neural Tangent Kernel Surrogate Models ICLR 2024