Rethinking Opinion Measurement Interfaces for Human-in-the-Loop Optimization
Human-in-the-loop optimization refers to systems that present choices to a human decision-maker and query their judgment to optimize system parameters iteratively. The user interface typically provides either an absolute rating scale or asks for a preferred option. However, these approaches can potentially suffer from calibration problems, inconsistencies, and completeness violations of user preferences in such a sequential evaluation. This paper revisits the design space of opinion measurement interfaces for human-in-the-loop optimization. We conducted a study (N=360) using text summarization and image color enhancement tasks to evaluate human sequential feedback in six representative op...
| Authors | Changkun Ou, Sven Mayer, Daniel Buschek et al. |
|---|---|
| Primary category | cs.HC |
| Published | 10 October 2026 |
| Last updated at source | 10 October 2026 |
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