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Last 30 days, Oct 4 – Nov 2
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Each repository’s best week of new stars, with the release published around it.
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- 1Owned by changkun now
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- modern-cpp-tutorialBest: 3rd by stars, 336 stars001
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Mentions
Rethinking Opinion Measurement Interfaces for Human-in-the-Loop Optimization Changkun Ou, Sven Mayer, Daniel Buschek, Andreas Butz arxiv.org [𝚌𝚜.𝙷𝙲 𝚌𝚜.𝙻𝙶] 💬Code: changkun/rankui t.co
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 opinion measurement interfaces. Based on our analysis, we recommend using a listwise approach to support sequential opinion measurement, which counterweighs individual rating and preferential choice limitations and conveys more information for subsequent use. We further discuss the trade-offs in different user interface designs and provide guidelines to inform future research. Comments: 29 pages. Written in 2022, published as last revised. Dataset, analysis scripts, and system source code: changkun/rankui