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Bibliographic Details
Main Authors: Rimbot, Thomas, Jaggi, Martin, Barba, Luis
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2503.00458
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Table of Contents:
  • In this work, we investigate the application of Machine Learning techniques to sport climbing. Expanding upon previous projects, we develop a visualization tool for move sequence evaluation on a given boulder. Then, we look into move sequence prediction from simple holds sequence information using three different Transformer models. While the results are not conclusive, they are a first step in this kind of approach and lay the ground for future work.