Papers by Shih-Heng Wang

1 papers
Systematic Analysis for Pretrained Language Model Priming for Parameter-Efficient Fine-tuning (2024.naacl-srw)

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Challenge: Parameter-efficient (PE) methods for adapting pre-trained language models to downstream tasks are still lacking in many cases.
Approach: They propose a general PE priming framework to enhance few-shot adaptation and generalization ability of PE methods.
Outcome: The proposed framework reveals that the best priming strategy facilitates adaptation to target tasks.

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