我可以问一个后续问题吗？了解对话对神经网络可解释性的益处

IF 3.4 3区计算机科学 Q2 COMPUTER SCIENCE, CYBERNETICS

International Journal of Human-Computer Interaction Pub Date : 2024-08-08 DOI:10.1080/10447318.2024.2364986

Tong Zhang, X. Jessie Yang, Boyang Li

引用次数: 0

摘要

可解释人工智能（XAI）研究旨在为不透明人工智能模型的决策过程提供洞察力。迄今为止，大多数 XAI 方法提供的都是一次性的静态解释，无法满足人工智能模型决策过程的需要。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

May I Ask a Follow-up Question? Understanding the Benefits of Conversations in Neural Network Explainability

Research in explainable AI (XAI) aims to provide insights into the decision-making process of opaque AI models. To date, most XAI methods offer one-off and static explanations, which cannot cater t...

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来源期刊

International Journal of Human-Computer Interaction 工程技术-计算机：控制论

CiteScore

9.00

自引率

21.30%

发文量

347

审稿时长

2 months

期刊介绍： The International Journal of Human-Computer Interaction addresses the cognitive, creative, social, health, and ergonomic aspects of interactive computing. It emphasizes the human element in relation to the systems and contexts in which humans perform, operate, network, and communicate, including mobile apps, social media, online communities, and digital accessibility. The journal publishes original articles including reviews and reappraisals of the literature, empirical studies, and quantitative and qualitative contributions to the theories and applications of HCI.