35 citations · 58 across the 17 of their papers we have counts for
8 papers · 1 filter
SubGCache: Accelerating Graph-based RAG with Subgraph-level KV Cache
Qiuyu Zhu, Liang Zhang, Qianxiong Xu +2
Graph-based retrieval-augmented generation (RAG) enables large language models (LLMs) to incorporate structured knowledge via graph retrieval as contextual input, enhancing more ac…
Efficient Multivariate Time Series Forecasting via Calibrated Language Models with Privileged Knowledge Distillation
Chenxi Liu, Hao Miao, Qianxiong Xu +5
Multivariate time series forecasting (MTSF) endeavors to predict future observations given historical data, playing a crucial role in time series data management systems. With adva…
Towards Cross-Modality Modeling for Time Series Analytics: A Survey in the LLM Era
Chenxi Liu, Shaowen Zhou, Qianxiong Xu +4
The proliferation of edge devices has generated an unprecedented volume of time series data across different domains, motivating various well-customized methods. Recently, Large La…
HierPromptLM: A Pure PLM-based Framework for Representation Learning on Heterogeneous Text-rich Networks
Qiuyu Zhu, Liang Zhang, Qianxiong Xu +1
Representation learning on heterogeneous text-rich networks (HTRNs), which consist of multiple types of nodes and edges with each node associated with textual information, is essen…
HHGT: Hierarchical Heterogeneous Graph Transformer for Heterogeneous Graph Representation Learning
Qiuyu Zhu, Liang Zhang, Qianxiong Xu +3
Despite the success of Heterogeneous Graph Neural Networks (HGNNs) in modeling real-world Heterogeneous Information Networks (HINs), challenges such as expressiveness limitations a…
TimeCMA: Towards LLM-Empowered Multivariate Time Series Forecasting via Cross-Modality Alignment
Chenxi Liu, Qianxiong Xu, Hao Miao +5
Multivariate time series forecasting (MTSF) aims to learn temporal dynamics among variables to forecast future time series. Existing statistical and deep learning-based methods suf…
Spatial-Temporal Large Language Model for Traffic Prediction
Chenxi Liu, Sun Yang, Qianxiong Xu +4
Traffic prediction, an essential component for intelligent transportation systems, endeavours to use historical data to foresee future traffic features at specific locations. Altho…
KITS: Inductive Spatio-Temporal Kriging with Increment Training Strategy
Qianxiong Xu, Cheng Long, Ziyue Li +3
Sensors are commonly deployed to perceive the environment. However, due to the high cost, sensors are usually sparsely deployed. Kriging is the tailored task to infer the unobserve…