105 citations · 478 across the 66 of their papers we have counts for
19 papers · 1 filter
Noise Matters: Diffusion Model-based Urban Mobility Generation with Collaborative Noise Priors
Yuheng Zhang, Yuan Yuan, Jingtao Ding +2
With global urbanization, the focus on sustainable cities has largely grown, driving research into equity, resilience, and urban planning, which often relies on mobility data. The…
Generalizing Hyperedge Expansion for Hyper-relational Knowledge Graph Modeling
Yu Liu, Shu Yang, Jingtao Ding +2
By representing knowledge in a primary triple associated with additional attribute-value qualifiers, hyper-relational knowledge graph (HKG) that generalizes triple-based knowledge…
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…
UniFlow: A Foundation Model for Unified Urban Spatio-Temporal Flow Prediction
Yuan Yuan, Jingtao Ding, Chonghua Han +3
Urban spatio-temporal flow prediction, encompassing traffic flows and crowd flows, is crucial for optimizing city infrastructure and managing traffic and emergency responses. Tradi…
Diffusion Transformers as Open-World Spatiotemporal Foundation Models
Yuan Yuan, Chonghua Han, Jingtao Ding +3
The urban environment is characterized by complex spatio-temporal dynamics arising from diverse human activities and interactions. Effectively modeling these dynamics is essential…
Symbolic regression via MDLformer-guided search: from minimizing prediction error to minimizing description length
Zihan Yu, Jingtao Ding, Yong Li +1
Symbolic regression, a task discovering the formula best fitting the given data, is typically based on the heuristical search. These methods usually update candidate formulas to ob…
Large-scale Urban Facility Location Selection with Knowledge-informed Reinforcement Learning
Hongyuan Su, Yu Zheng, Jingtao Ding +2
The facility location problem (FLP) is a classical combinatorial optimization challenge aimed at strategically laying out facilities to maximize their accessibility. In this paper,…
TDNetGen: Empowering Complex Network Resilience Prediction with Generative Augmentation of Topology and Dynamics
Chang Liu, Jingtao Ding, Yiwen Song +1
Predicting the resilience of complex networks, which represents the ability to retain fundamental functionality amidst external perturbations or internal failures, plays a critical…
A Population-to-individual Tuning Framework for Adapting Pretrained LM to On-device User Intent Prediction
Jiahui Gong, Jingtao Ding, Fanjin Meng +5
Mobile devices, especially smartphones, can support rich functions and have developed into indispensable tools in daily life. With the rise of generative AI services, smartphones c…
A Large-scale Benchmark Dataset for Commuting Origin-destination Matrix Generation
Can Rong, Jingtao Ding, Yan Liu +1
The commuting origin-destination~(OD) matrix is a critical input for urban planning and transportation, providing crucial information about the population residing in one region an…
UrbanWorld: An Urban World Model for 3D City Generation
Yu Shang, Yuming Lin, Yu Zheng +6
Cities, as the essential environment of human life, encompass diverse physical elements such as buildings, roads and vegetation, which continuously interact with dynamic entities l…
Spatio-Temporal Few-Shot Learning via Diffusive Neural Network Generation
Yuan Yuan, Chenyang Shao, Jingtao Ding +2
Spatio-temporal modeling is foundational for smart city applications, yet it is often hindered by data scarcity in many cities and regions. To bridge this gap, we propose a novel g…
Rumor Mitigation in Social Media Platforms with Deep Reinforcement Learning
Hongyuan Su, Yu Zheng, Jingtao Ding +2
Social media platforms have become one of the main channels where people disseminate and acquire information, of which the reliability is severely threatened by rumors widespread i…
MetroGNN: Metro Network Expansion with Reinforcement Learning
Hongyuan Su, Yu Zheng, Jingtao Ding +2
Selecting urban regions for metro network expansion to meet maximal transportation demands is crucial for urban development, while computationally challenging to solve. The expansi…
Social Physics Informed Diffusion Model for Crowd Simulation
Hongyi Chen, Jingtao Ding, Yong Li +2
Crowd simulation holds crucial applications in various domains, such as urban planning, architectural design, and traffic arrangement. In recent years, physics-informed machine lea…
Estimating On-road Transportation Carbon Emissions from Open Data of Road Network and Origin-destination Flow Data
Jinwei Zeng, Yu Liu, Jingtao Ding +2
Accounting for over 20% of the total carbon emissions, the precise estimation of on-road transportation carbon emissions is crucial for carbon emission monitoring and efficient mit…
A Comprehensive Survey on Artificial Intelligence for Complex Network: Potential, Methodology and Application
Jingtao Ding, Chang Liu, Yu Zheng +8
Complex networks pervade various real-world systems, from the natural environment to human societies. The essence of these networks is in their ability to transition and evolve fro…
UniST: A Prompt-Empowered Universal Model for Urban Spatio-Temporal Prediction
Yuan Yuan, Jingtao Ding, Jie Feng +2
Urban spatio-temporal prediction is crucial for informed decision-making, such as traffic management, resource optimization, and emergence response. Despite remarkable breakthrough…
Chain-of-Planned-Behaviour Workflow Elicits Few-Shot Mobility Generation in LLMs
Chenyang Shao, Fengli Xu, Bingbing Fan +4
The powerful reasoning capabilities of large language models (LLMs) have brought revolutionary changes to many fields, but their performance in human behaviour generation has not y…