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Make Me Happier: Evoking Emotions Through Image Diffusion Models., , , and . CoRR, (2024)Understanding the Interaction of Adversarial Training with Noisy Labels., , , , , , , and . CoRR, (2021)NoiLIn: Do Noisy Labels Always Hurt Adversarial Training?, , , , , , and . CoRR, (2021)XCode: Towards Cross-Language Code Representation with Large-Scale Pre-Training., , , , , , and . ACM Trans. Softw. Eng. Methodol., 31 (3): 52:1-52:44 (2022)Learning a robust foundation model against clean-label data poisoning attacks at downstream tasks., , , , and . Neural Networks, (January 2024)Reliable Adversarial Distillation with Unreliable Teachers., , , , , , , , and . ICLR, OpenReview.net, (2022)CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection., , , , , and . ICML, volume 139 of Proceedings of Machine Learning Research, page 11693-11703. PMLR, (2021)Fix-Filter-Fix: Intuitively Connect Any Models for Effective Bug Fixing., , , , and . EMNLP (1), page 3495-3504. Association for Computational Linguistics, (2021)RAMS-Trans: Recurrent Attention Multi-scale Transformer for Fine-grained Image Recognition., , , , , , and . ACM Multimedia, page 4239-4248. ACM, (2021)Robust Federated Recommendation System., , , , and . CoRR, (2020)