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Adversarial Learning

4854 directly classified papers

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General-purpose Adversarial Training for Enhanced Automatic Speech Recognition Model Generalization INTERSPEECH 2023
Poisoning Retrieval Corpora by Injecting Adversarial Passages EMNLP 2023
Towards Attack-tolerant Federated Learning via Critical Parameter Analysis ICCV 2023
Pay Attention to the Robustness of Chinese Minority Language Models! Syllable-level Textual Adversarial Attack on Tibetan Script ACL 2023
FIT BUT at SemEval-2023 Task 12: Sentiment Without Borders - Multilingual Domain Adaptation for Low-Resource Sentiment Classification ACL 2023
A Multilingual Evaluation of NER Robustness to Adversarial Inputs ACL 2023
On the Universal Adversarial Perturbations for Efficient Data-free Adversarial Detection ACL 2023
Neural Topic Modeling based on Cycle Adversarial Training and Contrastive Learning ACL 2023
G-Tuning: Improving Generalization of Pre-trained Language Models with Generative Adversarial Network ACL 2023
Adversarial Robustness of Prompt-based Few-Shot Learning for Natural Language Understanding ACL 2023
Effects of Human Adversarial and Affable Samples on BERT Generalization EMNLP 2023
PR-MCS: Perturbation Robust Metric for MultiLingual Image Captioning EMNLP 2023
Is Robustness Transferable across Languages in Multilingual Neural Machine Translation? EMNLP 2023
DeepBlueAI at PragTag-2023:Ensemble-based Text Classification Approaches under Limited Data Resources EMNLP 2023
Extending Adversarial Attacks to Produce Adversarial Class Probability Distributions JMLR 2023
Tractable and Near-Optimal Adversarial Algorithms for Robust Estimation in Contaminated Gaussian Models JMLR 2023
An Analysis of Robustness of Non-Lipschitz Networks JMLR 2023
The multimarginal optimal transport formulation of adversarial multiclass classification JMLR 2023
Robust Load Balancing with Machine Learned Advice JMLR 2023
A Relaxed Inertial Forward-Backward-Forward Algorithm for Solving Monotone Inclusions with Application to GANs JMLR 2023
DENL: Diverse Ensemble and Noisy Logits for Improved Robustness of Neural Networks ACML 2023
FLOAT: Fast Learnable Once-for-All Adversarial Training for Tunable Trade-Off Between Accuracy and Robustness WACV 2023
Outlier Robust Adversarial Training ACML 2023
RIATIG: Reliable and Imperceptible Adversarial Text-to-Image Generation With Natural Prompts CVPR 2023
Boosting Accuracy and Robustness of Student Models via Adaptive Adversarial Distillation CVPR 2023