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

IF 3.4 3区 计算机科学 Q2 COMPUTER SCIENCE, CYBERNETICS
Tong Zhang, X. Jessie Yang, Boyang Li
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引用次数: 0

Abstract

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...
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
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。
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来源期刊
International Journal of Human-Computer Interaction
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.
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