83 citations · 156 across the 12 of their papers we have counts for
12 papers
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…
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…
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…