Fine-Tuned Large Language Model for Visualization System: A Study on Self-Regulated Learning in Education

This paper presents Tailor-Mind, an LLM-powered interactive visualization system designed to support self-regulated learning for AI beginners through personalized tutoring, adaptive question recommendations, and knowledge mapping. The system fine-tunes LLMs for educational dialogue and scaffolding, with evaluation showing improved self-regulated learning outcomes.

Large Language Models (LLMs) have shown great potential in intelligent visualization systems, especially for domain-specific applications. Integrating LLMs into visualization systems presents challenges, and we categorize these challenges into three alignments: domain problems with LLMs, visualization with LLMs, and interaction with LLMs. To achieve these alignments, we propose a framework and outline a workflow to guide the application of fine-tuned LLMs to enhance visual interactions for domai

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