interpretable classification

AI Argues Differently: Distinct Argumentative and Linguistic Patterns of LLMs in Persuasive Contexts EMNLP 2025 A Robust Prototype-Based Network with Interpretable RBF Classifier Foundations AAAI 2025 Explaining Domain Shifts in Language: Concept Erasing for Interpretable Image Classification CVPR 2025 Interpretable Image Classification via Non-parametric Part Prototype Learning CVPR 2025 Interpretable point cloud classification using multiple instance learning ICCV 2025 QPM: Discrete Optimization for Globally Interpretable Image Classification ICLR 2025 Adversarial Text Generation using Large Language Models for Dementia Detection EMNLP 2024 Interpretable Image Classification with Adaptive Prototype-based Vision Transformers NeurIPS 2024 NeSyFOLD: A Framework for Interpretable Image Classification AAAI 2024 Context-Aware Feature Selection and Classification IJCAI 2023 Interpretable and Fair Boolean Rule Sets via Column Generation JMLR 2023 This Reads Like That: Deep Learning for Interpretable Natural Language Processing EMNLP 2023 Convolutional Dynamic Alignment Networks for Interpretable Classifications CVPR 2021 Uncertain Time Series Classification IJCAI 2021 ICAM: Interpretable Classification via Disentangled Representations and Feature Attribution Mapping NeurIPS 2020 LIBRE: Learning Interpretable Boolean Rule Ensembles AISTATS 2020 Transparent Classification with Multilayer Logical Perceptrons and Random Binarization AAAI 2020 Interpretable Rationale Augmented Charge Prediction System COLING 2018 Multi-value Rule Sets for Interpretable Classification with Feature-Efficient Representations NeurIPS 2018 A Bayesian Framework for Learning Rule Sets for Interpretable Classification JMLR 2017 Exact Rule Learning via Boolean Compressed Sensing ICML 2013 Projection Retrieval for Classification NeurIPS 2012