Summary of Performance Evaluation Of Lightweight Open-source Large Language Models in Pediatric Consultations: a Comparative Analysis, by Qiuhong Wei et al.
Performance Evaluation of Lightweight Open-source Large Language Models in Pediatric Consultations: A Comparative Analysis
by Qiuhong Wei, Ying Cui, Mengwei Ding, Yanqin Wang, Lingling Xiang, Zhengxiong Yao, Ceran Chen, Ying Long, Zhezhen Jin, Ximing Xu
First submitted to arxiv on: 16 Jul 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Computers and Society (cs.CY)
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| 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 investigates the potential applications of Large Language Models (LLMs) in pediatric healthcare settings. The authors compared four LLM models – ChatGLM3-6B, Vicuna-7B, Vicuna-13B, and ChatGPT-3.5 – on their ability to answer patient consultation questions from a public online medical forum. The results show that while the lightweight models demonstrated promising accuracy and completeness, they were outperformed by the larger-scale proprietary model, ChatGPT-3.5. Specifically, ChatGLM3-6B showed higher accuracy and completeness compared to Vicuna models, but was still surpassed by ChatGPT-3.5. The study also found that ChatGPT-3.5 demonstrated superior empathy and readability compared to the lightweight models. Overall, the findings suggest that while LLMs have potential applications in pediatric healthcare, there is a need for continued development efforts to bridge the gap between lightweight and large-scale proprietary models. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This study looks at how well different language models can answer medical questions from patients. The researchers tested four models on their ability to provide good answers. They found that one model, called ChatGPT-3.5, was better than the others at answering questions and being kind (empathy). Another model, ChatGLM3-6B, did well too, but wasn’t as good as ChatGPT-3.5. The study shows that language models can be helpful in healthcare, but there is still more work to do to make them even better. |
