105 citations · 171 across the 33 of their papers we have counts for
36 papers
UrbanWell: Benchmarking Multimodal Large Language Models for Spatio-Temporal Urban Wellbeing Analytics
Yanxin Xi, Xiang Su, Jie Feng +3
Understanding urban wellbeing from multimodal data requires integrating heterogeneous spatial and temporal signals, posing significant challenges for current multimodal large langu…
SpatialAct: Probing Spatial Reasoning-to-Action Capabilities of VLM Agents in 3D Scenes
Tianhui Liu, Jie Feng, Zhiheng Zheng +6
Humans can effortlessly perceive spatial layouts, form cognitive representations, reason about spatial relations, and translate such reasoning into actions in everyday 3D environme…
ARMove: Learning to Predict Human Mobility through Agentic Reasoning
Chuyue Wang, Jie Feng, Yuxi Wu +2
Human mobility prediction is a critical task but remains challenging due to its complexity and variability across populations and regions. Recently, large language models (LLMs) ha…
Enhancing Local Life Service Recommendation with Agentic Reasoning in Large Language Model
Shiteng Cao, Xiaochong Lan, Yuwei Du +4
Local life service recommendation is distinct from general recommendation scenarios due to its strong living need-driven nature. Fundamentally, accurately identifying a user's imme…
TrafficSimAgent: A Hierarchical Agent Framework for Autonomous Traffic Simulation with MCP Control
Yuwei Du, Jun Zhang, Jie Feng +3
Traffic simulation is important for transportation optimization and policy making. While existing simulators such as SUMO and MATSim offer fully-featured platforms and utilities, u…
RoadBench: Benchmarking MLLMs on Fine-Grained Spatial Understanding and Reasoning under Urban Road Scenarios
Jun Zhang, Xin Zhang, Jie Feng +5
Multimodal large language models (MLLMs) have demonstrated powerful capabilities in general spatial understanding and reasoning. However, their fine-grained spatial understanding a…
UrbanWorld2.0: A Multimodal Agentic Framework for Reality-Aligned 3D World Generation at City-Scale
Shengyuan Wang, Zhiheng Zheng, Yu Shang +6
The automated generation of high-fidelity, city-scale 3D environments remains a formidable challenge with profound academic and industrial implications. However, existing methods s…
AutoQual: An LLM Agent for Automated Discovery of Interpretable Features for Review Quality Assessment
Xiaochong Lan, Jie Feng, Yinxing Liu +2
Ranking online reviews by their intrinsic quality is a critical task for e-commerce platforms and information services, impacting user experience and business outcomes. However, qu…
CityRiSE: Reasoning Urban Socio-Economic Status in Large Vision-Language Models via Reinforcement Learning
Tianhui Liu, Hetian Pang, Xin Zhang +3
Urban socio-economic sensing plays a vital role in advancing global sustainable development goals. With the advent of Large Vision-Language Models (LVLMs), new opportunities have e…
Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning
Shengyuan Wang, Jie Feng, Tianhui Liu +2
Large language models (LLMs) possess extensive world knowledge, including geospatial knowledge, which has been successfully applied to various geospatial tasks such as mobility pre…
UrbanLLaVA: A Multi-modal Large Language Model for Urban Intelligence with Spatial Reasoning and Understanding
Jie Feng, Shengyuan Wang, Tianhui Liu +2
Urban research involves a wide range of scenarios and tasks that require the understanding of multi-modal data. Current methods often focus on specific data types and lack a unifie…
CAMS: A CityGPT-Powered Agentic Framework for Urban Human Mobility Simulation
Yuwei Du, Jie Feng, Jian Yuan +1
Human mobility simulation plays a crucial role in various real-world applications. Recently, to address the limitations of traditional data-driven approaches, researchers have expl…
AI Agent Behavioral Science
Lin Chen, Yunke Zhang, Jie Feng +13
Recent advances in large language models (LLMs) have enabled the development of AI agents that exhibit increasingly human-like behaviors, including planning, adaptation, and social…
Open-Set Living Need Prediction with Large Language Models
Xiaochong Lan, Jie Feng, Yizhou Sun +5
Living needs are the needs people generate in their daily lives for survival and well-being. On life service platforms like Meituan, user purchases are driven by living needs, maki…
LocalGPT: Benchmarking and Advancing Large Language Models for Local Life Services in Meituan
Xiaochong Lan, Jie Feng, Jiahuan Lei +2
Large language models (LLMs) have exhibited remarkable capabilities and achieved significant breakthroughs across various domains, leading to their widespread adoption in recent ye…
CityLens: Evaluating Large Vision-Language Models for Urban Socioeconomic Sensing
Tianhui Liu, Hetian Pang, Xin Zhang +5
Understanding urban socioeconomic conditions through visual data is a challenging yet essential task for sustainable urban development and policy planning. In this work, we introdu…
MoveGPT: Scaling Mobility Foundation Models with Spatially-Aware Mixture of Experts
Chonghua Han, Yuan Yuan, Jingtao Ding +3
The success of foundation models in language has inspired a new wave of general-purpose models for human mobility. However, existing approaches struggle to scale effectively due to…
UrbanPlanBench: A Comprehensive Urban Planning Benchmark for Evaluating Large Language Models
Yu Zheng, Longyi Liu, Yuming Lin +4
The advent of Large Language Models (LLMs) holds promise for revolutionizing various fields traditionally dominated by human expertise. Urban planning, a professional discipline th…
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,…
Defining and Evaluating Visual Language Models' Basic Spatial Abilities: A Perspective from Psychometrics
Wenrui Xu, Dalin Lyu, Weihang Wang +3
The Theory of Multiple Intelligences underscores the hierarchical nature of cognitive capabilities. To advance Spatial Artificial Intelligence, we pioneer a psychometric framework…
Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models
Fengli Xu, Qianyue Hao, Zefang Zong +17
Language has long been conceived as an essential tool for human reasoning. The breakthrough of Large Language Models (LLMs) has sparked significant research interest in leveraging…
Understanding World or Predicting Future? A Comprehensive Survey of World Models
Jingtao Ding, Yunke Zhang, Yu Shang +12
The concept of world models has garnered significant attention due to advancements in multimodal large language models such as GPT-4 and video generation models such as Sora, which…
OpenCity: A Scalable Platform to Simulate Urban Activities with Massive LLM Agents
Yuwei Yan, Qingbin Zeng, Zhiheng Zheng +5
Agent-based models (ABMs) have long been employed to explore how individual behaviors aggregate into complex societal phenomena in urban space. Unlike black-box predictive models,…
TrajAgent: An LLM-Agent Framework for Trajectory Modeling via Large-and-Small Model Collaboration
Yuwei Du, Jie Feng, Jie Zhao +1
Trajectory modeling, which includes research on trajectory data pattern mining and future prediction, has widespread applications in areas such as life services, urban transportati…