is like 11, 12, which is a much larger value. When you have a regression task, the goal of the model is to capture this variance and, in this task, most of the variance comes from the difficulty, which is why models end up focusing on the difficulty. Thus, the first task, a minor thing in the paper, but quite big thing outside of the paper, is to focus on actually scoring quality by disentangling the difficulty of the performance with the quality of the performance. And this is actually not straightforward to do, because if you scrape the base values or the difficulty from the score sheets, it actually reveals information that would only be available after the performance has been performed. It's leaking quality information, sometimes. What should be done instead? “Instead, I went back to the base value that have been established by the ISU, the International Skating Union,” Arushi explains. “And then I can start focusing on the problem that I actually wanted to focus on: increasing the interpretability of these models for the end user and athlete.” 14 DAILY WACV Monday Poster Presentation
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