3 papers
cs.CR2024
PersonaMark: Personalized LLM watermarking for model protection and user attribution
Yuehan Zhang, Peizhuo Lv, Yinpeng Liu +5
The rapid advancement of customized Large Language Models (LLMs) offers considerable convenience. However, it also intensifies concerns regarding the protection of copyright/confid…
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
From Model-centered to Human-Centered: Revision Distance as a Metric for Text Evaluation in LLMs-based Applications
Yongqiang Ma, Lizhi Qing, Jiawei Liu +5
Evaluating large language models (LLMs) is fundamental, particularly in the context of practical applications. Conventional evaluation methods, typically designed primarily for LLM…