# DesignGPT: Multi-Agent Collaboration in Design

arXiv: https://arxiv.org/abs/2311.11591 · HTML: https://mlsanity.com/paper/2311.11591/

## Key facts

- Cited by 17 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 19 references that are in the map.
- First posted on arXiv 20 Nov 2023.

## Builds on (most cited first, 5 of 5)

- [High-Resolution Image Synthesis with Latent Diffusion Models](https://mlsanity.com/paper/2112.10752/) (2021)
- [BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation](https://mlsanity.com/paper/2201.12086/) (2022)
- [Generative Agents: Interactive Simulacra of Human Behavior](https://mlsanity.com/paper/2304.03442/) (2023)
- [Sparks of Artificial General Intelligence: Early experiments with GPT-4](https://mlsanity.com/paper/2303.12712/) (2023)
- [MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework](https://mlsanity.com/paper/2308.00352/) (2023)

## Built on by (most cited first, 17 of 17)

- [Experiential Co-Learning of Software-Developing Agents](https://mlsanity.com/paper/2312.17025/) (2023)
- [Creativity in LLM-based Multi-Agent Systems: A Survey](https://mlsanity.com/paper/2505.21116/) (2025)
- [A Survey on Game Playing Agents and Large Models: Methods, Applications, and Challenges](https://mlsanity.com/paper/2403.10249/) (2024)
- [Iterative Experience Refinement of Software-Developing Agents](https://mlsanity.com/paper/2405.04219/) (2024)
- [ING-VP: MLLMs cannot Play Easy Vision-based Games Yet](https://mlsanity.com/paper/2410.06555/) (2024)
- [A Comprehensive Review of AI Agents: Transforming Possibilities in Technology and Beyond](https://mlsanity.com/paper/2508.11957/) (2025)
- [Toward Autonomous Engineering Design: A Knowledge-Guided Multi-Agent Framework](https://mlsanity.com/paper/2511.03179/) (2025)
- [Cross-Task Experiential Learning on LLM-based Multi-Agent Collaboration](https://mlsanity.com/paper/2505.23187/) (2025)
- [Parallelism Meets Adaptiveness: Scalable Documents Understanding in Multi-Agent LLM Systems](https://mlsanity.com/paper/2507.17061/) (2025)
- [JRE-L: Journalist, Reader, and Editor LLMs in the Loop for Science Journalism for the General Audience](https://mlsanity.com/paper/2501.16865/) (2025)
- [Co-Saving: Resource Aware Multi-Agent Collaboration for Software Development](https://mlsanity.com/paper/2505.21898/) (2025)
- [From Fragment to One Piece: A Survey on AI-Driven Graphic Design](https://mlsanity.com/paper/2503.18641/) (2025)
- [An Artificial Intelligence Approach for Interpreting Creative Combinational Designs](https://mlsanity.com/paper/2405.04985/) (2024)
- [When Discourse Stalls: Moving Past Five Semantic Stopsigns about Generative AI in Design Research](https://mlsanity.com/paper/2503.08565/) (2025)
- [Argus: A Multi-Agent Sensitive Information Leakage Detection Framework Based on Hierarchical Reference Relationships](https://mlsanity.com/paper/2512.08326/) (2025)
- [Agentic Risk-Aware Set-Based Engineering Design](https://mlsanity.com/paper/2604.16687/) (2026)
- [RocketAgent: A Long-Horizon Engineering Agent for Multidisciplinary Design of Liquid-Rocket Thrust Chambers](https://mlsanity.com/paper/2610.06044/) (2026)

## Abstract (arXiv)

Generative AI faces many challenges when entering the product design workflow, such as interface usability and interaction patterns. Therefore, based on design thinking and design process, we developed the DesignGPT multi-agent collaboration framework, which uses artificial intelligence agents to simulate the roles of different positions in the design company and allows human designers to collaborate with them in natural language. Experimental results show that compared with separate AI tools, DesignGPT improves the performance of designers, highlighting the potential of applying multi-agent systems that integrate design domain knowledge to product scheme design.