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May, 2025
利用思维链提示提升大语言模型的细粒度情感分类
Enhancing Granular Sentiment Classification with Chain-of-Thought Prompting in Large Language Models
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Vihaan Miriyala, Smrithi Bukkapatnam, Lavanya Prahallad
TL;DR
本研究解决了传统评分方法无法有效捕捉用户反馈中细微情感的问题。通过对2000份亚马逊应用程序评论的评估，提出了思维链提示的创新方法，显示出其在提升情感分析准确性方面的重要作用，准确率从84%提高至93%。
Abstract
We explore the use of
Chain-of-Thought
(CoT) prompting with
Large Language Models
(LLMs) to improve the accuracy of granular sentiment categorization in
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