most citedT2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models

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

collaborators

6 papers

cs.LG20261 cited

FaST: Efficient and Effective Long-Horizon Forecasting for Large-Scale Spatial-Temporal Graphs via Mixture-of-Experts

Yiji Zhao, Zihao Zhong, Ao Wang +5

Spatial-Temporal Graph (STG) forecasting on large-scale networks has garnered significant attention. However, existing models predominantly focus on short-horizon predictions and s…

cs.AI2025

Urban-R1: Reinforced MLLMs Mitigate Geospatial Biases for Urban General Intelligence

Qiongyan Wang, Xingchen Zou, Yutian Jiang +4

Rapid urbanization intensifies the demand for Urban General Intelligence (UGI), referring to AI systems that can understand and reason about complex urban environments. Recent stud…

cs.AI2025

MRGRP: Empowering Courier Route Prediction in Food Delivery Service with Multi-Relational Graph

Chang Liu, Huan Yan, Hongjie Sui +7

Instant food delivery has become one of the most popular web services worldwide due to its convenience in daily life. A fundamental challenge is accurately predicting courier route…

cs.LG20251 cited

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models

Yunfeng Ge, Jiawei Li, Yiji Zhao +6

Text-to-Time Series generation holds significant potential to address challenges such as data sparsity, imbalance, and limited availability of multimodal time series datasets acros…

cs.DB2025

Foundation Models for Spatio-Temporal Data Science: A Tutorial and Survey

Yuxuan Liang, Haomin Wen, Yutong Xia +6

Spatio-Temporal (ST) data science, which includes sensing, managing, and mining large-scale data across space and time, is fundamental to understanding complex systems in domains s…

cs.CV2025

Vision-Enhanced Time Series Forecasting via Latent Diffusion Models

Weilin Ruan, Siru Zhong, Haomin Wen +1

Diffusion models have recently emerged as powerful frameworks for generating high-quality images. While recent studies have explored their application to time series forecasting, t…