1 citations · 1 across the 7 of their papers we have counts for
7 papers
MPT: Multimodal Prompt Tuning for Zero-shot Instruction Learning
Taowen Wang, Yiyang Liu, James Chenhao Liang +11
Multimodal Large Language Models (MLLMs) demonstrate remarkable performance across a wide range of domains, with increasing emphasis on enhancing their zero-shot generalization cap…
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…
EAVE: Efficient Product Attribute Value Extraction via Lightweight Sparse-layer Interaction
Li Yang, Qifan Wang, Jianfeng Chi +7
Product attribute value extraction involves identifying the specific values associated with various attributes from a product profile. While existing methods often prioritize the d…
MVEB: Self-Supervised Learning with Multi-View Entropy Bottleneck
Liangjian Wen, Xiasi Wang, Jianzhuang Liu +1
Self-supervised learning aims to learn representation that can be effectively generalized to downstream tasks. Many self-supervised approaches regard two views of an image as both…
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…