# An Intelligent Assistant for Converting City Requirements to Formal Specification

arXiv: https://arxiv.org/abs/2206.07152 · HTML: https://mlsanity.com/paper/2206.07152/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 4 references that are in the map.
- First posted on arXiv 14 Jun 2022.

## Builds on (most cited first, 2 of 2)

- [CitySpec: An Intelligent Assistant System for Requirement Specification in Smart Cities](https://mlsanity.com/paper/2206.03132/) (2022)
- [A Novel Spatial-Temporal Specification-Based Monitoring System for Smart Cities](https://mlsanity.com/paper/2104.04904/) (2021)

## Built on by (most cited first, 4 of 4)

- [CitySpec with Shield: A Secure Intelligent Assistant for Requirement Formalization](https://mlsanity.com/paper/2302.09665/) (2023)
- [LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration](https://mlsanity.com/paper/2505.03985/) (2025)
- [Auto311: A Confidence-guided Automated System for Non-emergency Calls](https://mlsanity.com/paper/2312.14185/) (2023)
- [Empowering 9-1-1 Calltaking Training with Generative AI: Experiences and Lessons Learned](https://mlsanity.com/paper/2602.13241/) (2026)

## Abstract (arXiv)

As more and more monitoring systems have been deployed to smart cities, there comes a higher demand for converting new human-specified requirements to machine-understandable formal specifications automatically. However, these human-specific requirements are often written in English and bring missing, inaccurate, or ambiguous information. In this paper, we present CitySpec, an intelligent assistant system for requirement specification in smart cities. CitySpec not only helps overcome the language differences brought by English requirements and formal specifications, but also offers solutions to those missing, inaccurate, or ambiguous information. The goal of this paper is to demonstrate how CitySpec works. Specifically, we present three demos: (1) interactive completion of requirements in CitySpec; (2) human-in-the-loop correction while CitySepc encounters exceptions; (3) online learning in CitySpec.