out-of-distribution robustness

Refining Latent Homophilic Structures over Heterophilic Graphs for Robust Graph Convolution Networks AAAI 2024 Robust Image Denoising through Adversarial Frequency Mixup CVPR 2024 Towards Reliable Learning in the Wild: Generalization and Adaptation AAAI 2024 Are Data-Driven Explanations Robust Against Out-of-Distribution Data? CVPR 2023 Are Sample-Efficient NLP Models More Robust? ACL 2023 Can CNNs Be More Robust Than Transformers? ICLR 2023 Causal Triplet: An Open Challenge for Intervention-centric Causal Representation Learning CLeaR 2023 Compressing and Debiasing Vision-Language Pre-Trained Models for Visual Question Answering EMNLP 2023 Distilling Out-of-Distribution Robustness from Vision-Language Foundation Models NeurIPS 2023 Diversify and Disambiguate: Out-of-Distribution Robustness via Disagreement ICLR 2023 Effective Robustness against Natural Distribution Shifts for Models with Different Training Data NeurIPS 2023 Extensible Prompts for Language Models on Zero-shot Language Style Customization NeurIPS 2023 Fast Trainable Projection for Robust Fine-tuning NeurIPS 2023 Improve Video Representation with Temporal Adversarial Augmentation IJCAI 2023 Masked Images Are Counterfactual Samples for Robust Fine-Tuning CVPR 2023 PoseExaminer: Automated Testing of Out-of-Distribution Robustness in Human Pose and Shape Estimation CVPR 2023 Probing Out-of-Distribution Robustness of Language Models with Parameter-Efficient Transfer Learning ACL 2023 Revisiting Out-of-distribution Robustness in NLP: Benchmarks, Analysis, and LLMs Evaluations NeurIPS 2023 Robustness Challenges in Model Distillation and Pruning for Natural Language Understanding EACL 2023 Sparsity-Inducing Categorical Prior Improves Robustness of the Information Bottleneck AISTATS 2023 There is more than one kind of robustness: Fooling Whisper with adversarial examples Interspeech 2023 A Simple Data Mixing Prior for Improving Self-Supervised Learning CVPR 2022 C-Mixup: Improving Generalization in Regression NeurIPS 2022 Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity ICLR 2022 Neural Attentive Circuits NeurIPS 2022