model interpretability

XMD: An End-to-End Framework for Interactive Explanation-Based Debugging of NLP Models ACL 2023 AbductionRules: Training Transformers to Explain Unexpected Inputs ACL 2022 Accurate Shapley Values for explaining tree-based models AISTATS 2022 A Functional Information Perspective on Model Interpretation ICML 2022 Agree To Disagree: When Deep Learning Models With Identical Architectures Produce Distinct Explanations WACV 2022 AI Explainability 360: Impact and Design AAAI 2022 Analyzing Encoded Concepts in Transformer Language Models NAACL 2022 An Interactive Exploratory Tool for the Task of Hate Speech Detection NAACL 2022 Are Shortest Rationales the Best Explanations for Human Understanding? ACL 2022 Axiomatic Explanations for Visual Search, Retrieval, and Similarity Learning ICLR 2022 B-Cos Networks: Alignment Is All We Need for Interpretability CVPR 2022 Beyond Model Interpretability: On the Faithfulness and Adversarial Robustness of Contrastive Textual Explanations EMNLP 2022 BINAS: Bilinear Interpretable Neural Architecture Search ACML 2022 Can Rationalization Improve Robustness? NAACL 2022 CEBaB: Estimating the Causal Effects of Real-World Concepts on NLP Model Behavior NeurIPS 2022 Combining Feature and Instance Attribution to Detect Artifacts ACL 2022 CounteRGAN: Generating counterfactuals for real-time recourse and interpretability using residual GANs UAI 2022 Covered Information Disentanglement: Model Transparency via Unbiased Permutation Importance AAAI 2022 DEGREE: Decomposition Based Explanation for Graph Neural Networks ICLR 2022 Delivering Trustworthy AI through Formal XAI AAAI 2022 Discourse on ASR Measurement: Introducing the ARPOCA Assessment Tool ACL 2022 Discovering Latent Concepts Learned in BERT ICLR 2022 DISSECT: Disentangled Simultaneous Explanations via Concept Traversals ICLR 2022 Does Self-Rationalization Improve Robustness to Spurious Correlations? EMNLP 2022 Do Explanations Explain? Model Knows Best CVPR 2022