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Found 6 papers, 1 papers with code
Zero-shot Sequential Neuro-symbolic Reasoning for Automatically Generating Architecture Schematic Designs
This paper introduces a novel automated system for generating architecture schematic designs aimed at streamlining complex decision-making at the multifamily real estate development project's outset.
How Can Large Language Models Help Humans in Design and Manufacturing?
The advancement of Large Language Models (LLMs), including GPT-4, provides exciting new opportunities for generative design.
Self-Supervised Representation Learning for CAD
Assisting design with data-driven machine learning methods is hampered by lack of labeled data in CAD's native format; the parametric boundary representation (B-Rep).
Mates2Motion: Learning How Mechanical CAD Assemblies Work
We describe our work on inferring the degrees of freedom between mated parts in mechanical assemblies using deep learning on CAD representations.
Fabrication-Aware Reverse Engineering for Carpentry
We propose a novel method to generate fabrication blueprints from images of carpentered items.
AutoMate: A Dataset and Learning Approach for Automatic Mating of CAD Assemblies
To train our system, we compiled the first large scale dataset of BREP CAD assemblies, which we are releasing along with benchmark mate prediction tasks.
