most citedFrom Twitter to Reasoner: Understand Mobility Travel Modes and Sentiment Using Large Language Models

2 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2024

Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs

Zhaobin Mo, Qingyuan Liu, Baohua Yan +2

Spatiotemporal prediction over graphs (STPG) is crucial for transportation systems. In existing STPG models, an adjacency matrix is an important component that captures the relatio…

cs.LG20242 cited

From Twitter to Reasoner: Understand Mobility Travel Modes and Sentiment Using Large Language Models

Kangrui Ruan, Xinyang Wang, Xuan Di

Social media has become an important platform for people to express their opinions towards transportation services and infrastructure, which holds the potential for researchers to…

cs.CV2024

GenDDS: Generating Diverse Driving Video Scenarios with Prompt-to-Video Generative Model

Yongjie Fu, Yunlong Li, Xuan Di

Autonomous driving training requires a diverse range of datasets encompassing various traffic conditions, weather scenarios, and road types. Traditional data augmentation methods o…

math.OC2024

Graphon Mean Field Games with a Representative Player: Analysis and Learning Algorithm

Fuzhong Zhou, Chenyu Zhang, Xu Chen +1

We propose a discrete time graphon game formulation on continuous state and action spaces using a representative player to study stochastic games with heterogeneous interaction amo…

cs.AI2024

Learn to Tour: Operator Design For Solution Feasibility Mapping in Pickup-and-delivery Traveling Salesman Problem

Bowen Fang, Xu Chen, Xuan Di

This paper aims to develop a learning method for a special class of traveling salesman problems (TSP), namely, the pickup-and-delivery TSP (PDTSP), which finds the shortest tour al…