activity
20202026
most citedLarge Language Model for Participatory Urban Planning

13 citations · 35 across the 12 of their papers we have counts for

collaborators

12 papers

cs.AI2026

UrbanDS: A Graph-Guided LLM Multi-Agent System for Data-Intensive Urban Tasks

Zhilun Zhou, Jianghao Yu, Yuming Lin +4

Large language model (LLM) agents have been widely applied in automating data science tasks. However, existing methods typically rely on a limited set of provided datasets, and the…

cs.AI2026

ResMAS: Resilience Optimization in LLM-based Multi-agent Systems

Zhilun Zhou, Zihan Liu, Jiahe Liu +5

Large Language Model-based Multi-Agent Systems (LLM-based MAS), where multiple LLM agents collaborate to solve complex tasks, have shown impressive performance in many areas. Howev…

cs.AI2025★ 1 cited

MirrorMind: Empowering OmniScientist with the Expert Perspectives and Collective Knowledge of Human Scientists

Qingbin Zeng, Bingbing Fan, Zhiyu Chen +7

The emergence of AI Scientists has demonstrated remarkable potential in automating scientific research. However, current approaches largely conceptualize scientific discovery as a…

cs.AI2025

Rationality Check! Benchmarking the Rationality of Large Language Models

Zhilun Zhou, Jing Yi Wang, Nicholas Sukiennik +4

Large language models (LLMs), a recent advance in deep learning and machine intelligence, have manifested astonishing capacities, now considered among the most promising for artifi…

physics.soc-ph2025

A Survey of Physics-Informed AI for Complex Urban Systems

En Xu, Huandong Wang, Yunke Zhang +8

Urban systems are typical examples of complex systems, where the integration of physics-based modeling with artificial intelligence (AI) presents a promising paradigm for enhancing…

cs.AI2025

A Survey of Large Language Model-Powered Spatial Intelligence Across Scales: Advances in Embodied Agents, Smart Cities, and Earth Science

Jie Feng, Jinwei Zeng, Qingyue Long +15

Over the past year, the development of large language models (LLMs) has brought spatial intelligence into focus, with much attention on vision-based embodied intelligence. However,…

cs.CL2024★ 1 cited

Harnessing the Synergy between LLM Agents and Knowledge Graphs for Urban Socioeconomic Prediction

Zhilun Zhou, Jingyang Fan, Yu Liu +3

Socioeconomic prediction aims to leverage various urban data to predict the socioeconomic indicators of regions such as population and commercial activity level, which plays an imp…

cs.AI2024★ 13 cited

Large Language Model for Participatory Urban Planning

Zhilun Zhou, Yuming Lin, Depeng Jin +1

Participatory urban planning is the mainstream of modern urban planning that involves the active engagement of residents. However, the traditional participatory paradigm requires e…

cs.CL2024★ 4 cited

Large language model empowered participatory urban planning

Zhilun Zhou, Yuming Lin, Yong Li

Participatory urban planning is the mainstream of modern urban planning and involves the active engagement of different stakeholders. However, the traditional participatory paradig…

cs.AI2023★ 12 cited

Large Language Models Empowered Agent-based Modeling and Simulation: A Survey and Perspectives

Chen Gao, Xiaochong Lan, Nian Li +5

Agent-based modeling and simulation has evolved as a powerful tool for modeling complex systems, offering insights into emergent behaviors and interactions among diverse agents. In…

cs.AI2023★ 3 cited

Towards Generative Modeling of Urban Flow through Knowledge-enhanced Denoising Diffusion

Zhilun Zhou, Jingtao Ding, Yu Liu +2

Although generative AI has been successful in many areas, its ability to model geospatial data is still underexplored. Urban flow, a typical kind of geospatial data, is critical fo…

physics.soc-ph2020★ 1 cited

Disruption in the Chinese E-Commerce During COVID-19

Yuan Yuan, Muzhi Guan, Zhilun Zhou +4

The recent outbreak of the novel coronavirus (COVID-19) has infected millions of citizens worldwide and claimed many lives. This paper examines its impact on the Chinese e-commerce…