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Fine-tuning large-scale pretrained models is prohibitively expensive in terms of computational and memory costs.
The approximation of one matrix by another of lower rank
Carl Eckart and Gale Young · 1936
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Symmetric gauge functions and unitarily invariant norms
Leon Mirsky · 1960
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Delving deep into rectifiers: Surpassing human-level performance on imagenet classification, 2015
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Attention is all you need
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Gradient descent happens in a tiny subspace
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Glue: A multi-task benchmark and analysis platform for natural language understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R Bowman · 2018
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Parameter-efficient transfer learning for nlp
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Decoupled weight decay regularization, 2019
Ilya Loshchilov and Frank Hutter · 2019
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Intrinsic dimensionality explains the effectiveness of language model fine-tuning
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Lora: Low-rank adaptation of large language models, 2021
Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen · 2021
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Training verifiers to solve math word problems
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Xiang Lisa Li and Percy Liang · 2021
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