@inproceedings{d69d8cb85df14cb2b0dd5a01bf682a44,
title = "IvyGPT: InteractiVe Chinese Pathway Language Model in Medical Domain",
abstract = "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 inability to provide medical advice. We propose IvyGPT, an LLM based on LLaMA that is trained and fine-tuned with high-quality medical question-answer (QA) instances and Reinforcement Learning from Human Feedback (RLHF). In the training, we used QLoRA to handle 33 billion parameters on a small number of NVIDIA A100 (80 GB) GPUs. Experimental results show that IvyGPT has outperformed other medical GPT models. The online demo is available at http://81.71.71.157:52022. Our demo video can be found at https://youtu.be/O4D74pQh8Is.",
keywords = "Large language models, Medical, Reinforcement Learning",
author = "Rongsheng Wang and Yaofei Duan and Lam, {Chan Tong} and Jiexin Chen and Jiangsheng Xu and Haoming Chen and Xiaohong Liu and Pang, {Patrick Cheong Iao} and Tao Tan",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.; 3rd CAAI International Conference on Artificial Intelligence, CICAI 2023 ; Conference date: 22-07-2023 Through 23-07-2023",
year = "2024",
doi = "10.1007/978-981-99-9119-8_34",
language = "English",
isbn = "9789819991181",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "378--382",
editor = "Lu Fang and Jian Pei and Guangtao Zhai and Ruiping Wang",
booktitle = "Artificial Intelligence - Third CAAI International Conference, CICAI 2023, Revised Selected Papers",
address = "Germany",
}