论文标题
调解人：解释NLP模型行为的对话代理
Mediators: Conversational Agents Explaining NLP Model Behavior
论文作者
论文摘要
以人为中心的可解释人工智能（HCXAI）社区提出了将解释过程作为人与机器之间的对话进行构建。在该立场论文中，我们为中介者建立了基于文本的对话剂的逃避者，它们能够使用自然语言进行交互方式解释神经模型的行为。从自然语言处理（NLP）研究的角度来看，我们设计了这种调解人的蓝图，以进行情感分析的任务，并评估当前的研究对基于对话的解释的道路上有多远。
The human-centric explainable artificial intelligence (HCXAI) community has raised the need for framing the explanation process as a conversation between human and machine. In this position paper, we establish desiderata for Mediators, text-based conversational agents which are capable of explaining the behavior of neural models interactively using natural language. From the perspective of natural language processing (NLP) research, we engineer a blueprint of such a Mediator for the task of sentiment analysis and assess how far along current research is on the path towards dialogue-based explanations.
