@techreport{oai:ipsj.ixsq.nii.ac.jp:02007747,
 author = {叶内,琉聖 and 古宮,嘉那子},
 issue = {21},
 month = {Feb},
 note = {本研究ではRetreaval Augimented Generation(RAG)を用いて、源氏物語における古今和歌集からの引用検出を行った。昨今の大規模言語モデルには、聖書やギリシャ神話などの知識が多く備わっているが、いまだに日本の古典の知識は限定的である。そこで源氏物語部分と複数の引用元候補をLLMに入力し、実際に引用関係にあるかを判定させることで、引用を検出した。古今和歌集の和歌等が引用されている源氏物語369文に対してRAGを用いて引用検出を行い、Sentence BERTを用いた先行研究の引用検出システムとの性能比較を行った。実験の結果、53.7%のF値で引用を検出し、先行研究のシステムよりも性能が大幅に向上したことを示す。, This study applies Retrieval-Augmented Generation (RAG) to detect quotations from the Kokin Wakashu in The Tale of Genji. Although recent large language models possess extensive knowledge of sources such as the Bible and Greek mythology, their knowledge of Japanese classical literature remains limited. To address this issue, we input passages from The Tale of Genji together with multiple candidate source texts into a large language model and had it determine whether an actual quotation relationship exists, thereby detecting quotations. We applied RAG-based quotation detection to 369 sentences from The Tale of Genji that contain quotations from waka poems and other materials in the Kokin Wakashu. We compared its performance with that of a previous quotation detection system based on Sentence-BERT. Experimental results show that the proposed method achieved an F-score of 53.7%, representing a substantial improvement over the performance of the prior system.},
 title = {RAGを用いた源氏物語内の古今和歌集引用の検出},
 year = {2026}
}