Interpretability

Neural Additive Models: Interpretable Machine Learning with Neural Nets NeurIPS 2021 Neural Ensemble Search for Uncertainty Estimation and Dataset Shift NeurIPS 2021 Neural Language Models vs Wordnet-based Semantically Enriched Representation in CST Relation Recognition EACL 2021 NeuralLog: Natural Language Inference with Joint Neural and Logical Reasoning ACL 2021 Neural Natural Logic Inference for Interpretable Question Answering EMNLP 2021 Neural Population Geometry Reveals the Role of Stochasticity in Robust Perception NeurIPS 2021 Neural Prototype Trees for Interpretable Fine-Grained Image Recognition CVPR 2021 Neural Quality Estimation with Multiple Hypotheses for Grammatical Error Correction NAACL 2021 Neural-Symbolic Solver for Math Word Problems with Auxiliary Tasks ACL 2021 Neural Utility Functions AAAI 2021 Neuro-Symbolic Approaches for Text-Based Policy Learning EMNLP 2021 Neuro-Symbolic Reinforcement Learning with First-Order Logic EMNLP 2021 NLRG at SemEval-2021 Task 5: Toxic Spans Detection Leveraging BERT-based Token Classification and Span Prediction Techniques SemEval 2021 Noise or Signal: The Role of Image Backgrounds in Object Recognition ICLR 2021 Nonlinear Projection Based Gradient Estimation for Query Efficient Blackbox Attacks AISTATS 2021 On Attention Redundancy: A Comprehensive Study NAACL 2021 On Belief Change for Multi-Label Classifier Encodings IJCAI 2021 On Explainability of Graph Neural Networks via Subgraph Explorations ICML 2021 On Explaining Random Forests with SAT IJCAI 2021 On Generating Plausible Counterfactual and Semi-Factual Explanations for Deep Learning AAAI 2021 On Graph Neural Networks versus Graph-Augmented MLPs ICLR 2021 On Guaranteed Optimal Robust Explanations for NLP Models IJCAI 2021 On Locality of Local Explanation Models NeurIPS 2021 On Model Calibration for Long-Tailed Object Detection and Instance Segmentation NeurIPS 2021 On Recovering from Modeling Errors Using Testing Bayesian Networks ICML 2021