Zonghan Yang

Reducing Word Omission Errors in Neural Machine Translation: A Contrastive Learning Approach

2019

While neural machine translation (NMT) has achieved remarkable success, NMT systems are prone to make word omission errors. In this work, we propose a contrastive learning approach to reducing word omission errors in NMT. The …

Parameter-efficient fine-tuning of large-scale pre-trained language models

2023 · Nature Machine Intelligence

Abstract With the prevalence of pre-trained language models (PLMs) and the pre-training–fine-tuning paradigm, it has been continuously shown that larger models tend to yield better performance. However, as PLMs scale up, fine-tuning and storing all …