105 citations · 478 across the 66 of their papers we have counts for
10 papers · 1 filter
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…
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…
Alleviating Video-Length Effect for Micro-video Recommendation
Yuhan Quan, Jingtao Ding, Chen Gao +4
Micro-videos platforms such as TikTok are extremely popular nowadays. One important feature is that users no longer select interested videos from a set, instead they either watch t…
Spatio-temporal Diffusion Point Processes
Yuan Yuan, Jingtao Ding, Chenyang Shao +2
Spatio-temporal point process (STPP) is a stochastic collection of events accompanied with time and space. Due to computational complexities, existing solutions for STPPs compromis…
Road Planning for Slums via Deep Reinforcement Learning
Yu Zheng, Hongyuan Su, Jingtao Ding +2
Millions of slum dwellers suffer from poor accessibility to urban services due to inadequate road infrastructure within slums, and road planning for slums is critical to the sustai…
Complexity-aware Large Scale Origin-Destination Network Generation via Diffusion Model
Can Rong, Jingtao Ding, Zhicheng Liu +1
The Origin-Destination~(OD) networks provide an estimation of the flow of people from every region to others in the city, which is an important research topic in transportation, ur…
An Interdisciplinary Survey on Origin-destination Flows Modeling: Theory and Techniques
Can Rong, Jingtao Ding, Yong Li
Origin-destination (OD) flow modeling is an extensively researched subject across multiple disciplines, such as the investigation of travel demand in transportation and spatial int…
Robust Preference-Guided Denoising for Graph based Social Recommendation
Yuhan Quan, Jingtao Ding, Chen Gao +3
Graph Neural Network(GNN) based social recommendation models improve the prediction accuracy of user preference by leveraging GNN in exploiting preference similarity contained in s…
Knowledge-infused Contrastive Learning for Urban Imagery-based Socioeconomic Prediction
Yu Liu, Xin Zhang, Jingtao Ding +2
Monitoring sustainable development goals requires accurate and timely socioeconomic statistics, while ubiquitous and frequently-updated urban imagery in web like satellite/street v…
Learning to Simulate Daily Activities via Modeling Dynamic Human Needs
Yuan Yuan, Huandong Wang, Jingtao Ding +2
Daily activity data that records individuals' various types of activities in daily life are widely used in many applications such as activity scheduling, activity recommendation, a…