model interpretability

Exploring and Interacting with the Set of Good Sparse Generalized Additive Models NeurIPS 2023 Fairness Aware Counterfactuals for Subgroups NeurIPS 2023 Faithfulness Tests for Natural Language Explanations ACL 2023 Generalized Teacher Forcing for Learning Chaotic Dynamics ICML 2023 GLOBE-CE: A Translation Based Approach for Global Counterfactual Explanations ICML 2023 HiBug: On Human-Interpretable Model Debug NeurIPS 2023 “Honey, Tell Me What’s Wrong”, Global Explanation of Textual Discriminative Models through Cooperative Generation EMNLP 2023 IAEval: A Comprehensive Evaluation of Instance Attribution on Natural Language Understanding EMNLP 2023 Identifiable Contrastive Learning with Automatic Feature Importance Discovery NeurIPS 2023 Improving Interpretability via Explicit Word Interaction Graph Layer AAAI 2023 Incorporating Attribution Importance for Improving Faithfulness Metrics ACL 2023 Inference-Time Intervention: Eliciting Truthful Answers from a Language Model NeurIPS 2023 Inseq: An Interpretability Toolkit for Sequence Generation Models ACL 2023 Interpretability with full complexity by constraining feature information ICLR 2023 InterroLang: Exploring NLP Models and Datasets through Dialogue-based Explanations EMNLP 2023 Label-free Concept Bottleneck Models ICLR 2023 Leaping Into Memories: Space-Time Deep Feature Synthesis ICCV 2023 Learning Interpretable Temporal Properties from Positive Examples Only AAAI 2023 Learning to Receive Help: Intervention-Aware Concept Embedding Models NeurIPS 2023 Local Path Integration for Attribution AAAI 2023 Mitigating Bias: Enhancing Image Classification by Improving Model Explanations ACML 2023 NeuroX Library for Neuron Analysis of Deep NLP Models ACL 2023 NLP+Vis: NLP Meets Visualization EMNLP 2023 NxPlain: A Web-based Tool for Discovery of Latent Concepts EACL 2023 On the Impact of Knowledge Distillation for Model Interpretability ICML 2023