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Distiller: A Systematic Study of Model Distillation Methods in Natural Language Processing.

, , , , , and . SustaiNLP@EMNLP, page 119-133. Association for Computational Linguistics, (2021)

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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)Differentially Private Optimization on Large Model at Small Cost., , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 3192-3218. PMLR, (2023)DEM: Distribution Edited Model for Training with Mixed Data Distributions., , , , and . CoRR, (2024)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)Question Type Guided Attention in Visual Question Answering., , , and . ECCV (4), volume 11208 of Lecture Notes in Computer Science, page 158-175. Springer, (2018)On the accuracy and efficiency of group-wise clipping in differentially private optimization., , , , and . CoRR, (2023)Distiller: A Systematic Study of Model Distillation Methods in Natural Language Processing., , , , , and . SustaiNLP@EMNLP, page 119-133. Association for Computational Linguistics, (2021)Coupling public and private gradient provably helps optimization., , , , and . CoRR, (2023)Exploring the Role of Task Transferability in Large-Scale Multi-Task Learning., , , , , and . NAACL-HLT, page 2542-2550. Association for Computational Linguistics, (2022)