Evaluating Spatiotemporal Consistency in Automatically Generated Sewing Instructions

• URL: http://arxiv.org/abs/2509.24792v1
• Date: Mon, 29 Sep 2025 13:46:27 GMT
• Title: Evaluating Spatiotemporal Consistency in Automatically Generated Sewing Instructions
• Authors: Luisa Geiger, Mareike Hartmann, Michael Sullivan, Alexander Koller,
• Abstract summary: In this paper, we propose a metric for evaluating the soundness of sewing instructions.<n>We show that our proposed metric better correlates with manually-annotated error counts as well as human quality ratings.
• Score: 51.362705361059795
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In this paper, we propose a novel, automatic tree-based evaluation metric for LLM-generated step-by-step assembly instructions, that more accurately reflects spatiotemporal aspects of construction than traditional metrics such as BLEU and BERT similarity scores. We apply our proposed metric to the domain of sewing instructions, and show that our metric better correlates with manually-annotated error counts as well as human quality ratings, demonstrating our metric's superiority for evaluating the spatiotemporal soundness of sewing instructions. Further experiments show that our metric is more robust than traditional approaches against artificially-constructed counterfactual examples that are specifically constructed to confound metrics that rely on textual similarity.

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