2 papers
cs.CL2024
Low-Resource Multi-Granularity Academic Function Recognition Based on Multiple Prompt Knowledge
Jiawei Liu, Zi Xiong, Yi Jiang +4
Fine-tuning pre-trained language models (PLMs), e.g., SciBERT, generally requires large numbers of annotated data to achieve state-of-the-art performance on a range of NLP tasks in…
cs.CL2024
Enhance Robustness of Language Models Against Variation Attack through Graph Integration
Zi Xiong, Lizhi Qing, Yangyang Kang +5
The widespread use of pre-trained language models (PLMs) in natural language processing (NLP) has greatly improved performance outcomes. However, these models' vulnerability to adv…