# How Can Large Language Models Help Humans in Design and Manufacturing?

arXiv: https://arxiv.org/abs/2307.14377 · HTML: https://mlsanity.com/paper/2307.14377/

## Key facts

- Cited by 41 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Jul 2023.

## Built on by (most cited first, 30 of 41)

- [GenSim: Generating Robotic Simulation Tasks via Large Language Models](https://mlsanity.com/paper/2310.01361/) (2023)
- [Generating CAD Code with Vision-Language Models for 3D Designs](https://mlsanity.com/paper/2410.05340/) (2024)
- [GenSim2: Scaling Robot Data Generation with Multi-modal and Reasoning LLMs](https://mlsanity.com/paper/2410.03645/) (2024)
- [Text-to-CAD Generation Through Infusing Visual Feedback in Large Language Models](https://mlsanity.com/paper/2501.19054/) (2025)
- [CAD-Assistant: Tool-Augmented VLLMs as Generic CAD Task Solvers](https://mlsanity.com/paper/2412.13810/) (2024)
- [FlexCAD: Unified and Versatile Controllable CAD Generation with Fine-tuned Large Language Models](https://mlsanity.com/paper/2411.05823/) (2024)
- [DesignQA: A Multimodal Benchmark for Evaluating Large Language Models' Understanding of Engineering Documentation](https://mlsanity.com/paper/2404.07917/) (2024)
- [Video2Policy: Scaling up Manipulation Tasks in Simulation through Internet Videos](https://mlsanity.com/paper/2502.09886/) (2025)
- [Large Language Models for Manufacturing](https://mlsanity.com/paper/2410.21418/) (2024)
- [Generating Physically Stable and Buildable Brick Structures from Text](https://mlsanity.com/paper/2505.05469/) (2025)
- [3D-PreMise: Can Large Language Models Generate 3D Shapes with Sharp Features and Parametric Control?](https://mlsanity.com/paper/2401.06437/) (2024)
- [Large Language Model Agent as a Mechanical Designer](https://mlsanity.com/paper/2404.17525/) (2024)
- [CAD-Editor: A Locate-then-Infill Framework with Automated Training Data Synthesis for Text-Based CAD Editing](https://mlsanity.com/paper/2502.03997/) (2025)
- [Large Language Model-Enabled Multi-Agent Manufacturing Systems](https://mlsanity.com/paper/2406.01893/) (2024)
- [CADBench: A Multimodal Benchmark for AI-Assisted CAD Program Generation](https://mlsanity.com/paper/2605.10873/) (2026)
- [Towards Foundational AI Models for Additive Manufacturing: Language Models for G-Code Debugging, Manipulation, and Comprehension](https://mlsanity.com/paper/2309.02465/) (2023)
- [AutoTRIZ: Automating Engineering Innovation with TRIZ and Large Language Models](https://mlsanity.com/paper/2403.13002/) (2024)
- [Text2Robot: Evolutionary Robot Design from Text Descriptions](https://mlsanity.com/paper/2406.19963/) (2024)
- [RoboMorph: Evolving Robot Morphology using Large Language Models](https://mlsanity.com/paper/2407.08626/) (2024)
- [Industrial Language-Image Dataset (ILID): Adapting Vision Foundation Models for Industrial Settings](https://mlsanity.com/paper/2406.09637/) (2024)
- [Speech to Reality: On-Demand Production using Natural Language, 3D Generative AI, and Discrete Robotic Assembly](https://mlsanity.com/paper/2409.18390/) (2024)
- [A Large Language Model-Enabled Control Architecture for Dynamic Resource Capability Exploration in Multi-Agent Manufacturing Systems](https://mlsanity.com/paper/2505.22814/) (2025)
- [Embodied Co-Design for Rapidly Evolving Agents: Taxonomy, Frontiers, and Challenges](https://mlsanity.com/paper/2512.04770/) (2025)
- [Procedura: Agentic 3D Modeling with Procedural Control](https://mlsanity.com/paper/2608.26238/) (2026)
- [Slice-100K: A Multimodal Dataset for Extrusion-based 3D Printing](https://mlsanity.com/paper/2407.04180/) (2024)
- [Zero-shot Sequential Neuro-symbolic Reasoning for Automatically Generating Architecture Schematic Designs](https://mlsanity.com/paper/2402.00052/) (2024)
- [Generating Daylight-driven Architectural Design via Diffusion Models](https://mlsanity.com/paper/2404.13353/) (2024)
- [CRAFT: Designing Creative and Functional 3D Objects](https://mlsanity.com/paper/2412.03889/) (2024)
- [Human-in-the-Loop: Quantitative Evaluation of 3D Models Generation by Large Language Models](https://mlsanity.com/paper/2509.07010/) (2025)
- [Mediating Modes of Thought: LLM's for design scripting](https://mlsanity.com/paper/2411.14485/) (2024)

## Abstract (arXiv)

The advancement of Large Language Models (LLMs), including GPT-4, provides exciting new opportunities for generative design. We investigate the application of this tool across the entire design and manufacturing workflow. Specifically, we scrutinize the utility of LLMs in tasks such as: converting a text-based prompt into a design specification, transforming a design into manufacturing instructions, producing a design space and design variations, computing the performance of a design, and searching for designs predicated on performance. Through a series of examples, we highlight both the benefits and the limitations of the current LLMs. By exposing these limitations, we aspire to catalyze the continued improvement and progression of these models.