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Zheng, L., Chiang, W.L., Sheng, Y., Zhuang, S., Wu, Z., Zhuang, Y. and Stoica, I. (2024) Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena. Advances in Neural Information Processing Systems, 36, 1-12.

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• TITLE: Storyline Extraction of Document-Level Events Using Large Language Models

  AUTHORS: Ziyang Hu, Yaxiong Li

  KEYWORDS: Document-Level Storyline Extraction, Timeline, Large Language Models, Topological Structure of Storyline, Prompt Learning

  JOURNAL NAME: Journal of Computer and Communications, Vol.12 No.11, November 27, 2024

  ABSTRACT: This article proposes a document-level prompt learning approach using LLMs to extract the timeline-based storyline. Through verification tests on datasets such as ESCv1.2 and Timeline17, the results show that the prompt + one-shot learning proposed in this article works well. Meanwhile, our research findings indicate that although timeline-based storyline extraction has shown promising prospects in the practical applications of LLMs, it is still a complex natural language processing task that requires further research.