1 code implementation • 23 Apr 2024 • Shuhang Lin, Wenyue Hua, Lingyao Li, Che-Jui Chang, Lizhou Fan, Jianchao Ji, Hang Hua, Mingyu Jin, Jiebo Luo, Yongfeng Zhang
This novel system aims to simulate complex dynamic interactions among multiple agents, as well as between agents and their environments, over a period of time.
no code implementations • 24 Mar 2024 • Huizi Yu, Lizhou Fan, Lingyao Li, Jiayan Zhou, Zihui Ma, Lu Xian, Wenyue Hua, Sijia He, Mingyu Jin, Yongfeng Zhang, Ashvin Gandhi, Xin Ma
Large Language Models (LLMs) have rapidly become important tools in Biomedical and Health Informatics (BHI), enabling new ways to analyze data, treat patients, and conduct research.
1 code implementation • 4 Mar 2024 • Lizhou Fan, Wenyue Hua, Xiang Li, Kaijie Zhu, Mingyu Jin, Lingyao Li, Haoyang Ling, Jinkui Chi, Jindong Wang, Xin Ma, Yongfeng Zhang
Understanding the reasoning capabilities of Multimodal Large Language Models (MLLMs) is an important area of research.
1 code implementation • 1 Feb 2024 • Mingyu Jin, Qinkai Yu, Dong Shu, Chong Zhang, Lizhou Fan, Wenyue Hua, Suiyuan Zhu, Yanda Meng, Zhenting Wang, Mengnan Du, Yongfeng Zhang
Compared to traditional health management applications, our system has three main advantages: (1) It integrates health reports and medical knowledge into a large model to ask relevant questions to large language model for disease prediction; (2) It leverages a retrieval augmented generation (RAG) mechanism to enhance feature extraction; (3) It incorporates a semi-automated feature updating framework that can merge and delete features to improve accuracy of disease prediction.
1 code implementation • 22 Dec 2023 • Lizhou Fan, Wenyue Hua, Lingyao Li, Haoyang Ling, Yongfeng Zhang
Complex reasoning ability is one of the most important features of current LLMs, which has also been leveraged to play an integral role in complex decision-making tasks.
1 code implementation • 28 Nov 2023 • Wenyue Hua, Lizhou Fan, Lingyao Li, Kai Mei, Jianchao Ji, Yingqiang Ge, Libby Hemphill, Yongfeng Zhang
Can we avoid wars at the crossroads of history?
1 code implementation • 26 May 2023 • Lizhou Fan, Sara Lafia, Lingyao Li, Fangyuan Yang, Libby Hemphill
Data users need relevant context and research expertise to effectively search for and identify relevant datasets.
1 code implementation • 20 Apr 2023 • Lingyao Li, Lizhou Fan, Shubham Atreja, Libby Hemphill
To investigate this potential, we used ChatGPT and compared its performance with MTurker annotations for three frequently discussed concepts related to harmful content: Hateful, Offensive, and Toxic (HOT).
no code implementations • 3 Apr 2023 • Lizhou Fan, Lingyao Li, Zihui Ma, Sanggyu Lee, Huizi Yu, Libby Hemphill
Large language models (LLMs) are a class of language models that have demonstrated outstanding performance across a range of natural language processing (NLP) tasks and have become a highly sought-after research area, because of their ability to generate human-like language and their potential to revolutionize science and technology.
no code implementations • 23 May 2022 • Sara Lafia, Lizhou Fan, Libby Hemphill
The pipeline increases recall for literature to review for inclusion in data-related collections of publications and makes it possible to detect informal data references at scale.
no code implementations • 10 Mar 2022 • Lizhou Fan, Sara Lafia, David Bleckley, Elizabeth Moss, Andrea Thomer, Libby Hemphill
The librarian-in-the-loop paradigm is centered in the data work performed by ICPSR librarians, supporting broader efforts to build a more comprehensive bibliography of data-related literature that reflects the scholarly communities of research data users.