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Dive into Deep Learning for Natural Language Processing.

, , , , , , and . EMNLP/IJCNLP (2), Association for Computational Linguistics, (2019)

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Extreme Miscalibration and the Illusion of Adversarial Robustness., , , , , and . CoRR, (2024)Differentially Private Optimization on Large Model at Small Cost., , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 3192-3218. PMLR, (2023)Dive into Deep Learning for Natural Language Processing., , , , , , and . EMNLP/IJCNLP (2), Association for Computational Linguistics, (2019)Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual., , and . DeepLo@EMNLP-IJCNLP, page 132-142. Association for Computational Linguistics, (2019)Parameter and Data Efficient Continual Pre-training for Robustness to Dialectal Variance in Arabic., , , , , and . CoRR, (2022)Meta-learning via Language Model In-context Tuning., , , , and . CoRR, (2021)Large Language Models of Code Fail at Completing Code with Potential Bugs., , , , , , and . CoRR, (2023)Automatic Clipping: Differentially Private Deep Learning Made Easier and Stronger., , , and . CoRR, (2022)GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing., , , , , , , , , and 6 other author(s). J. Mach. Learn. Res., (2020)Efficient Long-Range Transformers: You Need to Attend More, but Not Necessarily at Every Layer., , , , and . EMNLP (Findings), page 2775-2786. Association for Computational Linguistics, (2023)