STYLE: Improving domain transferability of asking clarification questions in large language model powered conversational agents

• Main Authors: CHEN, Yue, HUANG, Chen, DENG, Yang, LEI, Wenqiang, JIN, Dingnan, LIU, Jia, CHUA, Tat-Seng
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Databases and Information Systems; Programming Languages and Compilers
• Online Access: https://ink.library.smu.edu.sg/sis_research/9234; https://ink.library.smu.edu.sg/context/sis_research/article/10234/viewcontent/2024.findings_acl.632.pdf
• Institution: Singapore Management University

Equipping a conversational search engine with strategies regarding when to ask clarification questions is becoming increasingly important across various domains. Attributing to the context understanding capability of LLMs and their access to domain-specific sources of knowledge, LLM-based clarificat...