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cs.CL2023
DialogStudio: Towards Richest and Most Diverse Unified Dataset Collection for Conversational AI
Jianguo Zhang, Kun Qian, Zhiwei Liu +7
Despite advancements in conversational AI, language models encounter challenges to handle diverse conversational tasks, and existing dialogue dataset collections often lack diversi…
cs.CL2022
AutoReply: Detecting Nonsense in Dialogue Introspectively with Discriminative Replies
Weiyan Shi, Emily Dinan, Adi Renduchintala +4
Existing approaches built separate classifiers to detect nonsense in dialogues. In this paper, we show that without external classifiers, dialogue models can detect errors in their…
cs.CL2022
Robots-Dont-Cry: Understanding Falsely Anthropomorphic Utterances in Dialog Systems
David Gros, Yu Li, Zhou Yu
Dialog systems are often designed or trained to output human-like responses. However, some responses may be impossible for a machine to truthfully say (e.g. "that movie made me cry…