2 papers
cs.LG2022
AGRO: Adversarial Discovery of Error-prone groups for Robust Optimization
Bhargavi Paranjape, Pradeep Dasigi, Vivek Srikumar +2
Models trained via empirical risk minimization (ERM) are known to rely on spurious correlations between labels and task-independent input features, resulting in poor generalization…
cs.CL2022
CORE: A Retrieve-then-Edit Framework for Counterfactual Data Generation
Tanay Dixit, Bhargavi Paranjape, Hannaneh Hajishirzi +1
Counterfactual data augmentation (CDA) -- i.e., adding minimally perturbed inputs during training -- helps reduce model reliance on spurious correlations and improves generalizatio…