32 citations · 101 across the 16 of their papers we have counts for
16 papers
LIONs: An Empirically Optimized Approach to Align Language Models
Xiao Yu, Qingyang Wu, Yu Li +1
Alignment is a crucial step to enhance the instruction-following and conversational abilities of language models. Despite many recent work proposing new algorithms, datasets, and t…
Curriculum-Driven Edubot: A Framework for Developing Language Learning Chatbots Through Synthesizing Conversational Data
Yu Li, Shang Qu, Jili Shen +2
Chatbots have become popular in educational settings, revolutionizing how students interact with material and how teachers teach. We present Curriculum-Driven EduBot, a framework f…
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…
DIONYSUS: A Pre-trained Model for Low-Resource Dialogue Summarization
Yu Li, Baolin Peng, Pengcheng He +3
Dialogue summarization has recently garnered significant attention due to its wide range of applications. However, existing methods for summarizing dialogues have limitations becau…
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…
Using Chatbots to Teach Languages
Yu Li, Chun-Yen Chen, Dian Yu +6
This paper reports on progress towards building an online language learning tool to provide learners with conversational experience by using dialog systems as conversation practice…