298 citations · 429 across the 17 of their papers we have counts for
17 papers
MPQ-DM: Mixed Precision Quantization for Extremely Low Bit Diffusion Models
Weilun Feng, Haotong Qin, Chuanguang Yang +7
Diffusion models have received wide attention in generation tasks. However, the expensive computation cost prevents the application of diffusion models in resource-constrained scen…
Context-Enhanced Multi-View Trajectory Representation Learning: Bridging the Gap through Self-Supervised Models
Tangwen Qian, Junhe Li, Yile Chen +4
Modeling trajectory data with generic-purpose dense representations has become a prevalent paradigm for various downstream applications, such as trajectory classification, travel t…
Relational Diffusion Distillation for Efficient Image Generation
Weilun Feng, Chuanguang Yang, Zhulin An +4
Although the diffusion model has achieved remarkable performance in the field of image generation, its high inference delay hinders its wide application in edge devices with scarce…
On the Integration of Spatial-Temporal Knowledge: A Lightweight Approach to Atmospheric Time Series Forecasting
Yisong Fu, Fei Wang, Zezhi Shao +6
Transformers have gained attention in atmospheric time series forecasting (ATSF) for their ability to capture global spatial-temporal correlations. However, their complex architect…
GinAR: An End-To-End Multivariate Time Series Forecasting Model Suitable for Variable Missing
Chengqing Yu, Fei Wang, Zezhi Shao +4
Multivariate time series forecasting (MTSF) is crucial for decision-making to precisely forecast the future values/trends, based on the complex relationships identified from histor…
Self-Improvement Programming for Temporal Knowledge Graph Question Answering
Zhuo Chen, Zhao Zhang, Zixuan Li +4
Temporal Knowledge Graph Question Answering (TKGQA) aims to answer questions with temporal intent over Temporal Knowledge Graphs (TKGs). The core challenge of this task lies in und…
AdapTraj: A Multi-Source Domain Generalization Framework for Multi-Agent Trajectory Prediction
Tangwen Qian, Yile Chen, Gao Cong +2
Multi-agent trajectory prediction, as a critical task in modeling complex interactions of objects in dynamic systems, has attracted significant research attention in recent years.…
Dynamic Frequency Domain Graph Convolutional Network for Traffic Forecasting
Yujie Li, Zezhi Shao, Yongjun Xu +3
Complex spatial dependencies in transportation networks make traffic prediction extremely challenging. Much existing work is devoted to learning dynamic graph structures among sens…
Exploring Progress in Multivariate Time Series Forecasting: Comprehensive Benchmarking and Heterogeneity Analysis
Zezhi Shao, Fei Wang, Yongjun Xu +10
Multivariate Time Series (MTS) analysis is crucial to understanding and managing complex systems, such as traffic and energy systems, and a variety of approaches to MTS forecasting…
DSformer: A Double Sampling Transformer for Multivariate Time Series Long-term Prediction
Chengqing Yu, Fei Wang, Zezhi Shao +3
Multivariate time series long-term prediction, which aims to predict the change of data in a long time, can provide references for decision-making. Although transformer-based model…
HUTFormer: Hierarchical U-Net Transformer for Long-Term Traffic Forecasting
Zezhi Shao, Fei Wang, Tao Sun +7
Traffic forecasting, which aims to predict traffic conditions based on historical observations, has been an enduring research topic and is widely recognized as an essential compone…
Spatial-Temporal Identity: A Simple yet Effective Baseline for Multivariate Time Series Forecasting
Zezhi Shao, Zhao Zhang, Fei Wang +2
Multivariate Time Series (MTS) forecasting plays a vital role in a wide range of applications. Recently, Spatial-Temporal Graph Neural Networks (STGNNs) have become increasingly po…
Pre-training Enhanced Spatial-temporal Graph Neural Network for Multivariate Time Series Forecasting
Zezhi Shao, Zhao Zhang, Fei Wang +1
Multivariate Time Series (MTS) forecasting plays a vital role in a wide range of applications. Recently, Spatial-Temporal Graph Neural Networks (STGNNs) have become increasingly po…
Decoupled Dynamic Spatial-Temporal Graph Neural Network for Traffic Forecasting
Zezhi Shao, Zhao Zhang, Wei Wei +4
We all depend on mobility, and vehicular transportation affects the daily lives of most of us. Thus, the ability to forecast the state of traffic in a road network is an important…
BiSyn-GAT+: Bi-Syntax Aware Graph Attention Network for Aspect-based Sentiment Analysis
Shuo Liang, Wei Wei, Xian-Ling Mao +2
Aspect-based sentiment analysis (ABSA) is a fine-grained sentiment analysis task that aims to align aspects and corresponding sentiments for aspect-specific sentiment polarity infe…
Heterogeneous Graph Neural Network with Multi-view Representation Learning
Zezhi Shao, Yongjun Xu, Wei Wei +3
Graph neural networks for heterogeneous graph embedding is to project nodes into a low-dimensional space by exploring the heterogeneity and semantics of the heterogeneous graph. Ho…
Exploiting Global Contextual Information for Document-level Named Entity Recognition
Zanbo Wang, Wei Wei, Xianling Mao +4
Most existing named entity recognition (NER) approaches are based on sequence labeling models, which focus on capturing the local context dependencies. However, the way of taking o…