Interpretability

AND: Audio Network Dissection for Interpreting Deep Acoustic Models ICML 2024 An Empirical Investigation Into Benchmarking Model Multiplicity for Trustworthy Machine Learning: A Case Study on Image Classification WACV 2024 An Entropy-based Text Watermarking Detection Method ACL 2024 A Neural Framework for Generalized Causal Sensitivity Analysis ICLR 2024 An Examination of the Robustness of Reference-Free Image Captioning Evaluation Metrics EACL 2024 An Information Theoretic Perspective on Conformal Prediction NeurIPS 2024 An Interactive Framework for Profiling News Media Sources NAACL 2024 An Interpretable Approach to the Solutions of High-Dimensional Partial Differential Equations AAAI 2024 An interpretable error correction method for enhancing code-to-code translation ICLR 2024 An Interpretable Evaluation of Entropy-based Novelty of Generative Models ICML 2024 An Investigation of Neuron Activation as a Unified Lens to Explain Chain-of-Thought Eliciting Arithmetic Reasoning of LLMs ACL 2024 An LLM Feature-based Framework for Dialogue Constructiveness Assessment EMNLP 2024 Annotation alignment: Comparing LLM and human annotations of conversational safety EMNLP 2024 Annotation and Classification of Relevant Clauses in Terms-and-Conditions Contracts COLING 2024 A Novel Metric for Measuring the Robustness of Large Language Models in Non-adversarial Scenarios EMNLP 2024 Antonym vs Synonym Distinction using InterlaCed Encoder NETworks (ICE-NET) EACL 2024 An Unsupervised Approach to Achieve Supervised-Level Explainability in Healthcare Records EMNLP 2024 A Peek into Token Bias: Large Language Models Are Not Yet Genuine Reasoners EMNLP 2024 A Perspectivist Corpus of Numbers in Social Judgements COLING 2024 A Polar coordinate system represents syntax in large language models NeurIPS 2024 Approximating the Shapley Value without Marginal Contributions AAAI 2024 A Preliminary Evaluation of Semantic Coherence and Cohesion in Aphasic and Non-Aphasic Discourse Across Test and Retest COLING 2024 A provable control of sensitivity of neural networks through a direct parameterization of the overall bi-Lipschitzness NeurIPS 2024 A Rate-Distortion View of Uncertainty Quantification ICML 2024 Arctique: An artificial histopathological dataset unifying realism and controllability for uncertainty quantification NeurIPS 2024