English(EN) Labadain-MedQA: A Tetun Medical QA Dataset for Fine-Tuning and Evaluating Large Language Models

使用LLM翻译开发了新的帝汶医疗问答数据集

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-04 05:00

研究人员开发了Labadain-MedQA，一个旨在提高帝汶语医疗问答能力的新数据集。该数据集通过使用Gemini 2.5 Flash将MedAlpaca和WikiDoc等现有医疗资源翻译成帝汶语创建，生成了超过39,000个问答对。评估表明，在医疗准确性和流畅性方面，人工翻译略优于LLM生成的翻译。在帝汶语翻译的医疗执照考试问题上，使用Gemma和Llama模型在该数据集上进行微调，显著提高了准确性，特别是使用QLoRA等参数高效微调技术时。 AI

影响促进了跨语言医疗知识的转移，并提高了LLM在低资源语言中的性能。

排序理由该集群是关于一篇研究论文，详细介绍了新数据集的创建及其评估。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

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arXiv cs.CL TIER_1 English(EN) · Gabriel de Jesus, S\'ergio Nunes · 2026-11-04 05:00

Labadain-MedQA: 用于微调和评估大型语言模型的 Tetun 医学问答数据集

arXiv:2611.00935v1 Announce Type: new Abstract: Advances in large language models (LLMs) have created opportunities for cross-lingual transfer of medical knowledge from high-resource to low-resource languages to support access to healthcare information. However, medical question-…

本文如何被排名

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Labadain-MedQA: 用于微调和评估大型语言模型的 Tetun 医学问答数据集

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