7 citations · 7 across the 4 of their papers we have counts for
5 papers
DeMa: Dual-Path Delay-Aware Mamba for Efficient Multivariate Time Series Analysis
Rui An, Haohao Qu, Wenqi Fan +2
Accurate and efficient multivariate time series (MTS) analysis is increasingly critical for a wide range of intelligent applications. Within this realm, Transformers have emerged a…
Damba-ST: Domain-Adaptive Mamba for Efficient Urban Spatio-Temporal Prediction
Rui An, Yifeng Zhang, Ziran Liang +4
Training urban spatio-temporal foundation models that generalize well across diverse regions and cities is critical for deploying urban services in unseen or data-scarce regions. R…
Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models
Xinmiao Hu, Chun Wang, Ruihe An +4
Multimodal Large Language Models (MLLMs) have demonstrated strong performance in visual understanding tasks, yet they often suffer from object hallucinations--generating descriptio…
iTFKAN: Interpretable Time Series Forecasting with Kolmogorov-Arnold Network
Ziran Liang, Rui An, Wenqi Fan +2
As time evolves, data within specific domains exhibit predictability that motivates time series forecasting to predict future trends from historical data. However, current deep for…
A Survey of Mamba
Haohao Qu, Liangbo Ning, Rui An +5
As one of the most representative DL techniques, Transformer architecture has empowered numerous advanced models, especially the large language models (LLMs) that comprise billions…