PlanGPT: Enhancing Urban Planning with Tailored Language Model and Efficient Retrieval
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Abstract (arXiv)
In the field of urban planning, general-purpose large language models often struggle to meet the specific needs of planners. Tasks like generating urban planning texts, retrieving related information, and evaluating planning documents pose unique challenges. To enhance the efficiency of urban professionals and overcome these obstacles, we introduce PlanGPT, the first specialized Large Language Model tailored for urban and spatial planning. Developed through collaborative efforts with institutions like the Chinese Academy of Urban Planning, PlanGPT leverages a customized local database retrieval framework, domain-specific fine-tuning of base models, and advanced tooling capabilities. Empirical tests demonstrate that PlanGPT has achieved advanced performance, delivering responses of superior quality precisely tailored to the intricacies of urban planning.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 39 of its 69 references that are in the map. First posted on arXiv 29 Feb 2024.
Builds on
39 of 69 references.
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Built on by
Citing papers per year: 2024: 4; 2025: 4.
8 papers.
- 2024UrbanLLM: Autonomous Urban Activity Planning and Management with Large Language Modelscited by 13
- 2024FANNO: Augmenting High-Quality Instruction Data with Open-Sourced LLMs Onlycited by 11
- 2024Self-Supervised Representation Learning for Geospatial Objects: A Surveycited by 8
- 2024Examining the Commitments and Difficulties Inherent in Multimodal Foundation Models for Street View Imagerycited by 4
- 2025Large Language Model Powered Intelligent Urban Agents: Concepts, Capabilities, and Applicationscited by 4
- 2025How to Auto-optimize Prompts for Domain Tasks? Adaptive Prompting and Reasoning through Evolutionary Domain Knowledge Adaptationcited by 4
- 2025Urban Computing in the Era of Large Language Modelscited by 2
- 2025PlanGPT-VL: Enhancing Urban Planning with Domain-Specific Vision-Language Modelscited by 2
- 2025How to Auto-optimize Prompts for Domain Tasks? Adaptive Prompting and Reasoning through Evolutionary Domain Knowledge Adaptation24 Oct 2025
- 2025Large Language Model Powered Intelligent Urban Agents: Concepts, Capabilities, and Applications1 Jul 2025
- 2025PlanGPT-VL: Enhancing Urban Planning with Domain-Specific Vision-Language Models20 May 2025
- 2025Urban Computing in the Era of Large Language Models2 Apr 2025
- 2024Examining the Commitments and Difficulties Inherent in Multimodal Foundation Models for Street View Imagery23 Aug 2024
- 2024Self-Supervised Representation Learning for Geospatial Objects: A Survey22 Aug 2024
- 2024FANNO: Augmenting High-Quality Instruction Data with Open-Sourced LLMs Only2 Aug 2024
- 2024UrbanLLM: Autonomous Urban Activity Planning and Management with Large Language Models18 Jun 2024