17 citations · 27 across the 6 of their papers we have counts for
5 papers · 1 filter
Enhancing Performance on Seen and Unseen Dialogue Scenarios using Retrieval-Augmented End-to-End Task-Oriented System
Jianguo Zhang, Stephen Roller, Kun Qian +6
End-to-end task-oriented dialogue (TOD) systems have achieved promising performance by leveraging sophisticated natural language understanding and natural language generation capab…
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…
User Adaptive Language Learning Chatbots with a Curriculum
Kun Qian, Ryan Shea, Yu Li +2
Along with the development of systems for natural language understanding and generation, dialog systems have been widely adopted for language learning and practicing. Many current…
Learning a Better Initialization for Soft Prompts via Meta-Learning
Yukun Huang, Kun Qian, Zhou Yu
Prompt tuning (PT) is an effective approach to adapting pre-trained language models to downstream tasks. Without a good initialization, prompt tuning doesn't perform well under few…
Domain Adaptive Dialog Generation via Meta Learning
Kun Qian, Zhou Yu
Domain adaptation is an essential task in dialog system building because there are so many new dialog tasks created for different needs every day. Collecting and annotating trainin…