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Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models.

, , , , , , and . ICLR, OpenReview.net, (2023)

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Adversarially Robust Distillation., , , and . CoRR, (2019)Witchcraft: Efficient PGD Attacks with Random Step Size., , , , , , and . ICASSP, page 3747-3751. IEEE, (2020)MetaBalance: High-Performance Neural Networks for Class-Imbalanced Data., , , , , and . CoRR, (2021)NEFTune: Noisy Embeddings Improve Instruction Finetuning., , , , , , , , , and 3 other author(s). CoRR, (2023)SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training., , , , and . CoRR, (2021)Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery., , , , , and . CoRR, (2023)STYX: Adaptive Poisoning Attacks Against Byzantine-Robust Defenses in Federated Learning., , , and . ICASSP, page 1-5. IEEE, (2023)Adversarial Examples Make Strong Poisons., , , , , and . NeurIPS, page 30339-30351. (2021)PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization., , , , , and . NeurIPS, (2022)Chroma-VAE: Mitigating Shortcut Learning with Generative Classifiers., , , and . NeurIPS, (2022)