Papers by Jiangyan Yi
NLoPT: N-gram Enhanced Low-Rank Task Adaptive Pre-training for Efficient Language Model Adaption (2024.lrec-main)
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| Challenge: | Pre-trained Language Models (PLMs) have superior performance on downstream tasks . however, conventional TAPT adjusts all parameters of the PLMs, which distorts the learned generic knowledge embedded in the original PLM's weights. |
| Approach: | They propose a two-step n-gram enhanced low-rank task adaptive pre-training method to customize a PLM to the downstream task. |
| Outcome: | The proposed method improves performance on six datasets from four domains. |