Oct 11, 2022 · We use this kernel view to propose an explanation for the success of parameter-efficient subspace-based fine-tuning methods.
We straightforwardly apply the kernel view of FT dynamics to formally analyze the success of fine- tuning methods that update in a low-rank subspace of model ...
This is the implementation for the paper A Kernel-Based View of Language Model Fine-tuning and can be used to compute kernel approximations for the ...
Feb 1, 2023 · Abstract: It has become standard to solve NLP tasks by fine-tuning pre-trained language models (LMs), especially in low-data settings.
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Jul 23, 2023 · Abstract. It has become standard to solve NLP tasks by fine-tuning pre-trained language models (LMs), especially in low-data settings.
It has become standard to solve NLP tasks by fine-tuning pre-trained language models (LMs), especially in low-data settings. There is minimal theoretical un ...
Jun 6, 2023 · Abstract. It has become standard to solve NLP tasks by fine-tuning pre-trained language models (LMs), especially in low-data settings.
It has become standard to solve NLP tasks by fine-tuning pre-trained language models (LMs), especially in low-data settings. There is minimal theoretical ...
It has become standard to solve NLP tasks by fine-tuning pre-trained language models (LMs), especially in low-data settings. There is minimal theoretical ...
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