Nepali Passport Question Answering: A Low-Resource Dataset for Public Service Applications

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On September 7, 2026, researchers published a low-resource dataset for questions and answers related to Nepali passports on the arXiv cs.LG platform. This dataset aims to support automated question-and-answer applications in public services, with special attention to model training requirements in scenarios where data resources are scarce.

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A arXiv cs.LG en 2026-09-07 12:00

针对尼泊尔语低资源语言缺乏标注数据与计算资源的挑战，研究团队构建了面向护照相关服务的配对式尼泊尔语问答数据集。该数据集用于训练和评估信息检索模型，并通过微调基于 Transformer 的嵌入模型实现语义相似度匹配。实验对比了细调模型与基线 BM25 算法，并实施了结合两者的混合检索方案。结果显示，细调 SBERT 模型性能优于 BM25，而多语言 E5 嵌入模型在所有测试模型中取得了最高的检索效果。