Abstract
Crochet, with its rich history and popularity, provides a creative and therapeutic outlet for millions across the globe, from many walks of life. However, crochet pattern creation and modification can be challenging for novice users, due to the spatial reasoning and structural understanding of stitches required. CrochetPARADE is a tool created to ease this process through pattern visualisation, but it uses a syntax that differs from standard notation and may not be intuitive to the average crocheter. This study explores the use of Large Language Models (LLMs) to translate user-generated crochet patterns into the CrochetPARADE syntax. The first structured, open-source collection of crochet patterns designed for machine learning applications was created, comprising user-generated patterns and their corresponding CrochetPARADE translations. Various approaches, including baseline, few-shot, and fine-tuning techniques, were evaluated with LLMs. The best results were achieved with fine-tuning DeepSeek-R1-Distill-Llama8b, reaching 74\% accuracy, which has the potential to significantly improve the accessibility and ease of crochet pattern creation for users with varying levels of expertise.
Original language | English |
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Publication status | Published - 21 May 2025 |
Event | Association for the Advancement of Artificial Intelligence Syposium on Human-AI Collaboration 2025: Exploring diversity of human cognitive abilities and varied AI models for hybrid intelligent systems - Heriot-Watt Campus, Dubai, United Arab Emirates Duration: 20 May 2025 → 22 May 2025 |
Conference
Conference | Association for the Advancement of Artificial Intelligence Syposium on Human-AI Collaboration 2025 |
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Abbreviated title | AAAI SuS 2025 |
Country/Territory | United Arab Emirates |
City | Dubai |
Period | 20/05/25 → 22/05/25 |