36 citations · 37 across the 3 of their papers we have counts for
3 papers
cs.CL2024
Fast Adversarial Training against Textual Adversarial Attacks
Yichen Yang, Xin Liu, Kun He
Many adversarial defense methods have been proposed to enhance the adversarial robustness of natural language processing models. However, most of them introduce additional pre-set…
cs.CV2023★ 1 cited
Big-model Driven Few-shot Continual Learning
Ziqi Gu, Chunyan Xu, Zihan Lu +3
Few-shot continual learning (FSCL) has attracted intensive attention and achieved some advances in recent years, but now it is difficult to again make a big stride in accuracy due…
cs.CL2023★ 36 cited
Large Language Models are Few-Shot Health Learners
Xin Liu, Daniel McDuff, Geza Kovacs +7
Large language models (LLMs) can capture rich representations of concepts that are useful for real-world tasks. However, language alone is limited. While existing LLMs excel at tex…