Papers by Youwei Liang
Generalizable and Stable Finetuning of Pretrained Language Models on Low-Resource Texts (2024.naacl-long)
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| Challenge: | Pretrained language models have advanced natural language processing tasks significantly, but finetuning them on low-resource datasets presents significant challenges such as instability and overfitting. |
| Approach: | They propose a regularization method based on attention-guided weight mixup for finetuning PLMs on low-resource datasets. |
| Outcome: | The proposed method improves generalization and combats overfitting on two splits of the training dataset. |