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English(EN) Nepali Passport Question Answering: A Low-Resource Dataset for Public Service Applications

新的尼泊尔护照问答数据集提高了检索性能

研究人员开发了一个专门针对尼泊尔护照相关服务的新问答数据集,解决了低资源语言资源稀缺的问题。该数据集用于微调基于Transformer的嵌入模型,包括SBERT和多语言E5,以改进信息检索。评估显示,微调后的SBERT模型超越了基线BM25,而多语言E5模型取得了最高的检索性能。 AI

影响 这项研究有助于改善低资源语言的信息获取,可能为更好的公共服务应用提供支持。

排序理由 学术论文,详细介绍了低资源语言信息检索的新数据集和模型评估。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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

新的尼泊尔护照问答数据集提高了检索性能

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33 / 100
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学术论文,详细介绍了低资源语言信息检索的新数据集和模型评估。[lever_c_demoted from research: ic=1 ai=1.0]
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paper, other
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Breaking (< 6h)
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Funghang Limbu Begha, Praveen Acharya, Bal Krishna Bal ·

    尼泊尔护照问答:面向公共服务应用的低资源数据集

    arXiv:2603.13320v2 Announce Type: replace-cross Abstract: Nepali, a low-resource language, faces significant challenges in building an effective information retrieval system due to the unavailability of annotated data and computational linguistic resources. In this study, we atte…