# Wiring diagram extraction and gluing: a case study in classifying figure skating jumps using 3D dataset

arXiv: https://arxiv.org/abs/2607.27598 · HTML: https://mlsanity.com/paper/2607.27598/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 16 references that are in the map.
- First posted on arXiv 30 Jul 2026.

## Builds on (most cited first, 4 of 4)

- [3D Pose-Based Temporal Action Segmentation for Figure Skating: A Fine-Grained and Jump Procedure-Aware Annotation Approach](https://mlsanity.com/paper/2408.16638/) (2024)
- [Automatic Edge Error Judgment in Figure Skating Using 3D Pose Estimation from a Monocular Camera and IMUs](https://mlsanity.com/paper/2310.17193/) (2023)
- [Quantifying analogy of concepts via ologs and wiring diagrams](https://mlsanity.com/paper/2402.01020/) (2024)
- [From data to concepts via wiring diagrams](https://mlsanity.com/paper/2511.20138/) (2025)

## Abstract (arXiv)

Hasse clustering is an algorithm that extracts common patterns in sequential data and represents them in graphical forms. As the number of expected clusters grows, however, the algorithm can become infeasible to run due to combinatorial complexity. In this article, we describe a theory of gluing wiring diagrams, allowing iterative applications of Hasse clustering to achieve the same result as a single application. We test our theory in the context of classifying videos of figure skating jumps.