most citedPredicting Large-scale Urban Network Dynamics with Energy-informed Graph Neural Diffusion

2 citations · 2 across the 1 of their papers we have counts for

collaborators

5 papers

cs.LG20252 cited

Predicting Large-scale Urban Network Dynamics with Energy-informed Graph Neural Diffusion

Tong Nie, Jian Sun, Wei Ma

Networked urban systems facilitate the flow of people, resources, and services, and are essential for economic and social interactions. These systems often involve complex processe…

cs.AI2025

Seeking to Collide: Online Safety-Critical Scenario Generation for Autonomous Driving with Retrieval Augmented Large Language Models

Yuewen Mei, Tong Nie, Jian Sun +1

Simulation-based testing is crucial for validating autonomous vehicles (AVs), yet existing scenario generation methods either overfit to common driving patterns or operate in an of…

cs.AI2025

Exploring the Roles of Large Language Models in Reshaping Transportation Systems: A Survey, Framework, and Roadmap

Tong Nie, Jian Sun, Wei Ma

Modern transportation systems face pressing challenges due to increasing demand, dynamic environments, and heterogeneous information integration. The rapid evolution of Large Langu…

cs.LG2025

Collaborative Imputation of Urban Time Series through Cross-city Meta-learning

Tong Nie, Wei Ma, Jian Sun +2

Urban time series, such as mobility flows, energy consumption, and pollution records, encapsulate complex urban dynamics and structures. However, data collection in each city is im…

cs.LG2025

LLM-attacker: Enhancing Closed-loop Adversarial Scenario Generation for Autonomous Driving with Large Language Models

Yuewen Mei, Tong Nie, Jian Sun +1

Ensuring and improving the safety of autonomous driving systems (ADS) is crucial for the deployment of highly automated vehicles, especially in safety-critical events. To address t…