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Nearest Neighbor Search for Summarization of Japanese Judgment Documents
Akito Shimbo, Yuta Sugawara, Hiroaki Yamada, Takenobu Tokunaga
335 - 340
10.3233/FAIA230984
Research Article
Frontiers in Artificial Intelligence and Applications
Volume 379: Legal Knowledge and Information Systems
Abstract

With the increasing demand for summarizing Japanese judgment documents, the automatic generation of high-quality summaries by large language models (LLMs) is expected. We propose a method to select exemplars using the nearest neighbor search for the one-shot learning method. The experiments showed our method outperforms baseline methods.

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