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Papers
Quantifying and Improving the Robustness of Retrieval-Augmented Language Models Against Spurious Features in Grounding Data
ACL 2026
Robustness Quantification for Discriminative Models: a New Robustness Metric and its Application to Dynamic Classifier Selection
UAI 2026
Probabilistic Robustness Quantification of Neural Networks
AAAI 2021
POPQORN: Quantifying Robustness of Recurrent Neural Networks
ICML 2019