51 citations · 64 across the 9 of their papers we have counts for
9 papers
TimeCNN: Refining Cross-Variable Interaction on Time Point for Time Series Forecasting
Ao Hu, Dongkai Wang, Yong Dai +7
Time series forecasting is extensively applied across diverse domains. Transformer-based models demonstrate significant potential in modeling cross-time and cross-variable interact…
XMoE: Sparse Models with Fine-grained and Adaptive Expert Selection
Yuanhang Yang, Shiyi Qi, Wenchao Gu +3
Sparse models, including sparse Mixture-of-Experts (MoE) models, have emerged as an effective approach for scaling Transformer models. However, they often suffer from computational…
Enhancing Multivariate Time Series Forecasting with Mutual Information-driven Cross-Variable and Temporal Modeling
Shiyi Qi, Liangjian Wen, Yiduo Li +5
Recent advancements have underscored the impact of deep learning techniques on multivariate time series forecasting (MTSF). Generally, these techniques are bifurcated into two cate…
PDETime: Rethinking Long-Term Multivariate Time Series Forecasting from the perspective of partial differential equations
Shiyi Qi, Zenglin Xu, Yiduo Li +4
Recent advancements in deep learning have led to the development of various models for long-term multivariate time-series forecasting (LMTF), many of which have shown promising res…
BadCS: A Backdoor Attack Framework for Code search
Shiyi Qi, Yuanhang Yang, Shuzhzeng Gao +2
With the development of deep learning (DL), DL-based code search models have achieved state-of-the-art performance and have been widely used by developers during software developme…
Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping
Zhe Li, Shiyi Qi, Yiduo Li +1
Introduction: Long-term time series forecasting (LTSF) has gained significant attention in recent years. While various specialized designs exist for capturing temporal dependency,…
Once is Enough: A Light-Weight Cross-Attention for Fast Sentence Pair Modeling
Yuanhang Yang, Shiyi Qi, Chuanyi Liu +3
Transformer-based models have achieved great success on sentence pair modeling tasks, such as answer selection and natural language inference (NLI). These models generally perform…
A Closer Look into Transformer-Based Code Intelligence Through Code Transformation: Challenges and Opportunities
Yaoxian Li, Shiyi Qi, Cuiyun Gao +4
Transformer-based models have demonstrated state-of-the-art performance in many intelligent coding tasks such as code comment generation and code completion. Previous studies show…
Dynamically Relative Position Encoding-Based Transformer for Automatic Code Edit
Shiyi Qi, Yaoxian Li, Cuiyun Gao +4
Adapting Deep Learning (DL) techniques to automate non-trivial coding activities, such as code documentation and defect detection, has been intensively studied recently. Learning t…