3.7k citations · 13.3k across the 162 of their papers we have counts for
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cs.CL2021★ 30 cited
How Should Pre-Trained Language Models Be Fine-Tuned Towards Adversarial Robustness?
Xinhsuai Dong, Luu Anh Tuan, Min Lin +2
The fine-tuning of pre-trained language models has a great success in many NLP fields. Yet, it is strikingly vulnerable to adversarial examples, e.g., word substitution attacks usi…
cs.CL2020★ 129 cited
ConvBERT: Improving BERT with Span-based Dynamic Convolution
Zihang Jiang, Weihao Yu, Daquan Zhou +3
Pre-trained language models like BERT and its variants have recently achieved impressive performance in various natural language understanding tasks. However, BERT heavily relies o…