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Robustness

133 papers

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Papers

Interpreting the Robustness of Neural NLP Models to Textual Perturbations ACL 2022
On Length Divergence Bias in Textual Matching Models ACL 2022
3DeformRS: Certifying Spatial Deformations on Point Clouds CVPR 2022
Bounded Adversarial Attack on Deep Content Features CVPR 2022
Robust Image Forgery Detection Over Online Social Network Shared Images CVPR 2022
PixMix: Dreamlike Pictures Comprehensively Improve Safety Measures CVPR 2022
Certified Patch Robustness via Smoothed Vision Transformers CVPR 2022
Robustness of Fusion-based Multimodal Classifiers to Cross-Modal Content Dilutions EMNLP 2022
Machine Translation Robustness to Natural Asemantic Variation EMNLP 2022
Investigating the Robustness of Natural Language Generation from Logical Forms via Counterfactual Samples EMNLP 2022
Does Self-Rationalization Improve Robustness to Spurious Correlations? EMNLP 2022
Towards Robust Visual Question Answering: Making the Most of Biased Samples via Contrastive Learning EMNLP 2022
Exploring Robustness of Prefix Tuning in Noisy Data: A Case Study in Financial Sentiment Analysis EMNLP 2022
A Geometric Perspective towards Neural Calibration via Sensitivity Decomposition NIPS 2021
Power up! Robust Graph Convolutional Network via Graph Powering AAAI 2021
Adaptive Verifiable Training Using Pairwise Class Similarity AAAI 2021
Exploring the Vulnerability of Deep Neural Networks: A Study of Parameter Corruption AAAI 2021
Exploring the Efficacy of Automatically Generated Counterfactuals for Sentiment Analysis ACL 2021
Learning from the Worst: Dynamically Generated Datasets to Improve Online Hate Detection ACL 2021
Towards Robustness of Text-to-SQL Models against Synonym Substitution ACL 2021
Simpler Certified Radius Maximization by Propagating Covariances CVPR 2021
On Robustness and Transferability of Convolutional Neural Networks CVPR 2021
Quality-Agnostic Image Recognition via Invertible Decoder CVPR 2021
Achieving Model Robustness through Discrete Adversarial Training EMNLP 2021
Evaluating the Robustness of Neural Language Models to Input Perturbations EMNLP 2021