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English(EN) KSE-Web: An Analysis of Hybrid Retrieval and LLM-Assisted Query Expansion for Low-Resource Khmer Semantic Search

LLM辅助查询扩展在高棉语语义搜索中效果不一

研究人员开发了KSE-Web系统,旨在改善高棉语的语义搜索,该语言因数据有限和混合语言使用而面临挑战。研究评估了包括BM25、密集检索和混合方法在内的各种检索方法,以及使用Qwen2.5模型的LLM辅助查询扩展。结果表明,传统的BM25表现最佳,混合方法显示出相当的有效性。虽然LLM扩展并未普遍改善结果,但较大的Qwen2.5模型显示出潜力,尽管直接扩展也引入了主题漂移和噪声等问题。 AI

影响 强调了LLM辅助检索在低资源语言中的潜力和局限性,为未来的模型开发提供信息。

排序理由 学术论文,详细介绍了针对特定NLP任务的新系统和实验分析。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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LLM辅助查询扩展在高棉语语义搜索中效果不一

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学术论文,详细介绍了针对特定NLP任务的新系统和实验分析。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Nimol Thuon ·

    KSE-Web:一种用于低资源高棉语语义搜索的混合检索和LLM辅助查询扩展分析

    arXiv:2608.21365v1 Announce Type: cross Abstract: As a low-resource language, Khmer presents several retrieval challenges, including limited annotated data, ambiguous word boundaries, weak support in multilingual embedding models, and frequent mixed Khmer-English usage. This pape…