spurious correlation

Examining and Combating Spurious Features under Distribution Shift ICML 2021 Explaining the Efficacy of Counterfactually Augmented Data ICLR 2021 Exploring the Efficacy of Automatically Generated Counterfactuals for Sentiment Analysis ACL 2021 Fairness via Representation Neutralization NeurIPS 2021 Generative Interventions for Causal Learning CVPR 2021 How Does Counterfactually Augmented Data Impact Models for Social Computing Constructs? EMNLP 2021 Increasing Robustness to Spurious Correlations using Forgettable Examples EACL 2021 Influence Tuning: Demoting Spurious Correlations via Instance Attribution and Instance-Driven Updates EMNLP 2021 Just Train Twice: Improving Group Robustness without Training Group Information ICML 2021 Learn to Expect the Unexpected: Probably Approximately Correct Domain Generalization AISTATS 2021 Leveraging Sparse Linear Layers for Debuggable Deep Networks ICML 2021 Mitigating Biases in Toxic Language Detection through Invariant Rationalization ACL 2021 Natural Adversarial Examples CVPR 2021 Noise or Signal: The Role of Image Backgrounds in Object Recognition ICLR 2021 On Calibration and Out-of-Domain Generalization NeurIPS 2021 Recovering Latent Causal Factor for Generalization to Distributional Shifts NeurIPS 2021 Refining Language Models with Compositional Explanations NeurIPS 2021 Robustness to Spurious Correlations in Text Classification via Automatically Generated Counterfactuals AAAI 2021 Saliency is a Possible Red Herring When Diagnosing Poor Generalization ICLR 2021 Selecting Data Augmentation for Simulating Interventions ICML 2021 Selective Classification Can Magnify Disparities Across Groups ICLR 2021 Shortcutted Commonsense: Data Spuriousness in Deep Learning of Commonsense Reasoning EMNLP 2021 Spurious Correlations in Cross-Topic Argument Mining ACL 2021 Towards Robust Classification Model by Counterfactual and Invariant Data Generation CVPR 2021 Uncovering Main Causalities for Long-tailed Information Extraction EMNLP 2021