Understand User Opinions of Large Language Models via LLM-Powered In-the-Moment User Experience Interviews
Which large language model (LLM) is better?Every evaluation tells a story, but what do users really think about current LLMs?This paper presents CLUE, an LLM-powered interviewer that conducts in-the-moment user experience interviews, right after users interact with LLMs, and automatically gathers insights about user opinions from massive interview logs.We conduct a study with thousands of users to understand user opinions on mainstream LLMs, recruiting users to first chat with a target LLM and then be interviewed by CLUE.Our experiments demonstrate that CLUE captures interesting user opinions, e.g., the bipolar views on the displayed reasoning process of DeepSeek-R1 and demands for information freshness and multi-modality.
Authors
- Cassandra A. Cohen
- Tevin Wang (ORCID: https://orcid.org/0009-0008-1517-1212)
- Sarah Li
- Mei Liu (ORCID: https://orcid.org/0000-0003-1156-2722)
- Chenyan Xiong
Publication Details
- Published
- 2025-01-01
- DOI
- https://doi.org/10.18653/v1/2025.findings-acl.714
- Primary Topic
- Topic Modeling
- Type
- article
- Field-Weighted Citation Impact
- 0.00