Fine-Tuning Small Language Models (SLMs) for Autonomous Web-based Geographical Information Systems (AWebGIS)

Mahdi Nazari Ashani; Ali Asghar Alesheikh; Saba Kazemi; Kimya Kheirkhah; Yasin Mohammadi; Fatemeh Rezaie; Amir Mahdi Manafi; Hedieh Zarkesh

arXiv · 2508.04846

Fine-Tuning Small Language Models (SLMs) for Autonomous Web-based Geographical Information Systems (AWebGIS)

Mahdi Nazari Ashani·Ali Asghar Alesheikh·Saba Kazemi·Kimya Kheirkhah·Yasin Mohammadi·Fatemeh Rezaie·Amir Mahdi Manafi·Hedieh Zarkesh

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Abstract

Autonomous web-based geographical information systems (AWebGIS) aim to perform geospatial operations from natural language input, providing intuitive, intelligent, and hands-free interaction. However, most current solutions rely on cloud-based large language models (LLMs), which require continuous internet access and raise users' privacy and scalability issues due to centralized server processing. This study compares three approaches to enabling AWebGIS: (1) a fully-automated online method using cloud-based LLMs (e.g., Cohere); (2) a semi-automated offline method using classical machine learning classifiers such as support vector machine and random forest; and (3) a fully autonomous offline (client-side) method based on a fine-tuned small language model (SLM), specifically T5-small model, executed in the client's web browser. The third approach, which leverages SLMs, achieved the highest accuracy among all methods, with an exact matching accuracy of 0.93, Levenshtein similarity of 0.99, and recall-oriented understudy for gisting evaluation ROUGE-1 and ROUGE-L scores of 0.98. Crucially, this client-side computation strategy reduces the load on backend servers by offloading processing to the user's device, eliminating the need for server-based inference. These results highlight the feasibility of browser-executable models for AWebGIS solutions.

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BibTeX RIS

Mahdi Nazari Ashani, Ali Asghar Alesheikh, Saba Kazemi, Kimya Kheirkhah, Yasin Mohammadi, Fatemeh Rezaie, Amir Mahdi Manafi, Hedieh Zarkesh. 2025-08-06. Fine-Tuning Small Language Models (SLMs) for Autonomous Web-based Geographical Information Systems (AWebGIS). https://arxiv.org/abs/2508.04846

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