This research introduces a novel multimodal approach that integrates visual feedback into Large Language Models to improve text-to-CAD generation accuracy and quality.

• Leverages both parametric sequences and rendered visual objects to create a comprehensive CAD generation system
• Implements an innovative visual perception mechanism that allows LLMs to "see" and refine CAD models
• Achieves superior performance compared to traditional sequential-signal-only approaches
• Demonstrates practical applications in engineering design workflows by reducing the expertise barrier for CAD model creation

This breakthrough matters for engineering because it significantly reduces the technical expertise required to create precise CAD models, potentially democratizing access to engineering design tools and accelerating prototyping processes.

Text-to-CAD Generation Through Infusing Visual Feedback in Large Language Models