45 citations · 171 across the 21 of their papers we have counts for
11 papers · 1 filter
Ophtha-LLaMA2: A Large Language Model for Ophthalmology
Huan Zhao, Qian Ling, Yi Pan +14
In recent years, pre-trained large language models (LLMs) have achieved tremendous success in the field of Natural Language Processing (NLP). Prior studies have primarily focused o…
Holistic Evaluation of GPT-4V for Biomedical Imaging
Zhengliang Liu, Hanqi Jiang, Tianyang Zhong +47
In this paper, we present a large-scale evaluation probing GPT-4V's capabilities and limitations for biomedical image analysis. GPT-4V represents a breakthrough in artificial gener…
Evaluating Large Language Models in Ophthalmology
Jason Holmes, Shuyuan Ye, Yiwei Li +11
Purpose: The performance of three different large language models (LLMS) (GPT-3.5, GPT-4, and PaLM2) in answering ophthalmology professional questions was evaluated and compared wi…
Evaluating multiple large language models in pediatric ophthalmology
Jason Holmes, Rui Peng, Yiwei Li +10
IMPORTANCE The response effectiveness of different large language models (LLMs) and various individuals, including medical students, graduate students, and practicing physicians, i…
ChatRadio-Valuer: A Chat Large Language Model for Generalizable Radiology Report Generation Based on Multi-institution and Multi-system Data
Tianyang Zhong, Wei Zhao, Yutong Zhang +39
Radiology report generation, as a key step in medical image analysis, is critical to the quantitative analysis of clinically informed decision-making levels. However, complex and d…
Review of Large Vision Models and Visual Prompt Engineering
Jiaqi Wang, Zhengliang Liu, Lin Zhao +18
Visual prompt engineering is a fundamental technology in the field of visual and image Artificial General Intelligence, serving as a key component for achieving zero-shot capabilit…
Evaluating Large Language Models for Radiology Natural Language Processing
Zhengliang Liu, Tianyang Zhong, Yiwei Li +43
The rise of large language models (LLMs) has marked a pivotal shift in the field of natural language processing (NLP). LLMs have revolutionized a multitude of domains, and they hav…
Instruction-ViT: Multi-Modal Prompts for Instruction Learning in ViT
Zhenxiang Xiao, Yuzhong Chen, Lu Zhang +14
Prompts have been proven to play a crucial role in large language models, and in recent years, vision models have also been using prompts to improve scalability for multiple downst…
ChatABL: Abductive Learning via Natural Language Interaction with ChatGPT
Tianyang Zhong, Yaonai Wei, Li Yang +13
Large language models (LLMs) such as ChatGPT have recently demonstrated significant potential in mathematical abilities, providing valuable reasoning paradigm consistent with human…
When Brain-inspired AI Meets AGI
Lin Zhao, Lu Zhang, Zihao Wu +11
Artificial General Intelligence (AGI) has been a long-standing goal of humanity, with the aim of creating machines capable of performing any intellectual task that humans can do. T…
Mask-guided BERT for Few Shot Text Classification
Wenxiong Liao, Zhengliang Liu, Haixing Dai +11
Transformer-based language models have achieved significant success in various domains. However, the data-intensive nature of the transformer architecture requires much labeled dat…