Interpretability

IST-Unbabel 2021 Submission for the Explainable Quality Estimation Shared Task EMNLP 2021 Iterative Bounding MDPs: Learning Interpretable Policies via Non-Interpretable Methods AAAI 2021 It’s Commonsense, isn’t it? Demystifying Human Evaluations in Commonsense-Enhanced NLG Systems EACL 2021 “It seemed like an annoying woman”: On the Perception and Ethical Considerations of Affective Language in Text-Based Conversational Agents CoNLL 2021 “It’s our fault!”: Insights Into Users’ Understanding and Interaction With an Explanatory Collaborative Dialog System CoNLL 2021 KACE: Generating Knowledge Aware Contrastive Explanations for Natural Language Inference ACL 2021 KDExplainer: A Task-oriented Attention Model for Explaining Knowledge Distillation IJCAI 2021 Keep CALM and Improve Visual Feature Attribution ICCV 2021 K-N-MOMDPs: Towards Interpretable Solutions for Adaptive Management AAAI 2021 KW-ATTN: Knowledge Infused Attention for Accurate and Interpretable Text Classification NAACL 2021 L2C: Describing Visual Differences Needs Semantic Understanding of Individuals EACL 2021 Language Model Augmented Relevance Score ACL 2021 Language Modelling as a Multi-Task Problem EACL 2021 Larger-Context Tagging: When and Why Does It Work? NAACL 2021 “Laughing at you or with you”: The Role of Sarcasm in Shaping the Disagreement Space EACL 2021 Learning Accurate and Interpretable Decision Rule Sets from Neural Networks AAAI 2021 Learning A Risk-Aware Trajectory Planner From Demonstrations Using Logic Monitor CoRL 2021 Learning by Fixing: Solving Math Word Problems with Weak Supervision AAAI 2021 Learning Decision Trees Recurrently Through Communication CVPR 2021 Learning from the Best: Rationalizing Predictions by Adversarial Information Calibration AAAI 2021 Learning Interpretable Concept Groups in CNNs IJCAI 2021 Learning Logic Rules for Document-Level Relation Extraction EMNLP 2021 Learning Models for Actionable Recourse NeurIPS 2021 Learning Prediction Intervals for Model Performance AAAI 2021 Learning to Cascade: Confidence Calibration for Improving the Accuracy and Computational Cost of Cascade Inference Systems AAAI 2021