We Don't Know How to Assess LLM Contributions in VIS/HCI
Submissions of original research that use Large Language Models (LLMs) or that study their behavior, suddenly account for a sizable portion of works submitted and accepted to visualization (VIS) conferences and similar venues in human-computer interaction (HCI). In this brief position paper, I argue that reviewers are relatively unprepared to evaluate these submissions effectively. To support this conjecture I reflect on my experience serving on four program committees for VIS and HCI conferences over the past year. I will describe common reviewer critiques that I observed and highlight how these critiques influence the review process. I also raise some concerns about these critiques that could limit applied LLM research to all but the best-resourced labs. While I conclude with suggestions for evaluating research contributions that incorporate LLMs, the ultimate goal of this position paper is to simulate a discussion on the review process and its challenges.
Authors
- Anamaria Crisan (ORCID: https://orcid.org/0000-0003-3445-3414)
Institutions
- University of Waterloo (CA)
Publication Details
- Published
- 2024-10-14
- DOI
- https://doi.org/10.1109/beliv64461.2024.00018
- Citations
- 3
- Primary Topic
- Artificial Intelligence in Law
- Type
- article
- Field-Weighted Citation Impact
- 6.69