Interpretability

Large Language Models Are Clinical Reasoners: Reasoning-Aware Diagnosis Framework with Prompt-Generated Rationales AAAI 2024 Large Language Models Are Not Robust Multiple Choice Selectors ICLR 2024 Large language models fail to derive atypicality inferences in a human-like manner ACL 2024 Large Language Models Must Be Taught to Know What They Don’t Know NeurIPS 2024 Large Language Models Relearn Removed Concepts ACL 2024 Large Language Models Sensitivity to The Order of Options in Multiple-Choice Questions NAACL 2024 Latent Concept-based Explanation of NLP Models EMNLP 2024 Latent Logic Tree Extraction for Event Sequence Explanation from LLMs ICML 2024 Latent Space Symmetry Discovery ICML 2024 Layer-Aware Analysis of Catastrophic Overfitting: Revealing the Pseudo-Robust Shortcut Dependency ICML 2024 Layerwise Change of Knowledge in Neural Networks ICML 2024 LayoutLLM: Layout Instruction Tuning with Large Language Models for Document Understanding CVPR 2024 LCGbank: A Corpus of Syntactic Analyses Based on Proof Nets COLING 2024 Learnable Privacy Neurons Localization in Language Models ACL 2024 Learning Accurate and Interpretable Decision Trees UAI 2024 Learning Bidirectional Morphological Inflection like Humans COLING 2024 Learning Decision Trees and Forests with Algorithmic Recourse ICML 2024 Learning Discrete Concepts in Latent Hierarchical Models NeurIPS 2024 Learning Exceptional Subgroups by End-to-End Maximizing KL-Divergence ICML 2024 Learning Fine-Grained Grounded Citations for Attributed Large Language Models ACL 2024 Learning from Integral Losses in Physics Informed Neural Networks ICML 2024 Learning interpretable control inputs and dynamics underlying animal locomotion ICLR 2024 Learning Interpretable Legal Case Retrieval via Knowledge-Guided Case Reformulation EMNLP 2024 Learning Intrinsic Dimension via Information Bottleneck for Explainable Aspect-based Sentiment Analysis COLING 2024 Learning Performance Maximizing Ensembles with Explainability Guarantees AAAI 2024