mlsanityData to 7 Oct 2026

PlanGPT: Enhancing Urban Planning with Tailored Language Model and Efficient Retrieval

arXiv 2402.19273 ↗First posted 29 Feb 2024cs.CLcited by 8

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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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27 more
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Citing papers per year: 2024: 4; 2025: 4.

8 papers.