Summary of Medgo: a Chinese Medical Large Language Model, by Haitao Zhang and Bo An
MedGo: A Chinese Medical Large Language Model
by Haitao Zhang, Bo An
First submitted to arxiv on: 27 Oct 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper presents MedGo, a Chinese medical large language model designed to enhance medical services by leveraging generative capabilities. To address limitations of current models, which struggle with accuracy and narrow capabilities in medical applications, the authors trained MedGo using high-quality unsupervised data, supervised data, and preference alignment data. The model was evaluated on the public CBLUE benchmark and a manually constructed dataset ClinicalQA. Results show that MedGo achieved promising performance across various Chinese medical information processing tasks, ranking first on the CBLUE evaluation and outperforming its base model Qwen2 on ClinicalQA. These results demonstrate MedGo’s strong information processing capabilities in the medical field. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper makes a big breakthrough in artificial intelligence research! The scientists created a special kind of computer program called MedGo that can help doctors and hospitals do their jobs better. Right now, computers are not very good at helping with medical tasks like answering questions or making decisions. But MedGo is different – it was trained to be really good at understanding Chinese medical information and making smart decisions. The scientists tested MedGo on two big datasets and found that it did a great job! It even beat its own base model in some areas. This means that MedGo could help hospitals make better decisions and improve patient care. |
Keywords
» Artificial intelligence » Alignment » Large language model » Supervised » Unsupervised
