5 citations · 14 across the 6 of their papers we have counts for
6 papers
Fine-Tuning Medical Language Models for Enhanced Long-Contextual Understanding and Domain Expertise
Qimin Yang, Rongsheng Wang, Jiexin Chen +2
Large Language Models (LLMs) have been widely applied in various professional fields. By fine-tuning the models using domain specific question and answer datasets, the professional…
CARZero: Cross-Attention Alignment for Radiology Zero-Shot Classification
Haoran Lai, Qingsong Yao, Zihang Jiang +4
The advancement of Zero-Shot Learning in the medical domain has been driven forward by using pre-trained models on large-scale image-text pairs, focusing on image-text alignment. H…
LLM-Detector: Improving AI-Generated Chinese Text Detection with Open-Source LLM Instruction Tuning
Rongsheng Wang, Haoming Chen, Ruizhe Zhou +6
ChatGPT and other general large language models (LLMs) have achieved remarkable success, but they have also raised concerns about the misuse of AI-generated texts. Existing AI-gene…
Aurora:Activating Chinese chat capability for Mixtral-8x7B sparse Mixture-of-Experts through Instruction-Tuning
Rongsheng Wang, Haoming Chen, Ruizhe Zhou +8
Existing research has demonstrated that refining large language models (LLMs) through the utilization of machine-generated instruction-following data empowers these models to exhib…
DetectGPT-SC: Improving Detection of Text Generated by Large Language Models through Self-Consistency with Masked Predictions
Rongsheng Wang, Qi Li, Sihong Xie
General large language models (LLMs) such as ChatGPT have shown remarkable success, but it has also raised concerns among people about the misuse of AI-generated texts. Therefore,…
IvyGPT: InteractiVe Chinese pathwaY language model in medical domain
Rongsheng Wang, Yaofei Duan, ChanTong Lam +6
General large language models (LLMs) such as ChatGPT have shown remarkable success. However, such LLMs have not been widely adopted for medical purposes, due to poor accuracy and i…