Multivariate time series forecasting is widely applied in fields such as transportation, energy, and finance. However, the data commonly suffers from issues of multi-scale characteristics, weak correlations, and noise interference, which limit the predictive performance of existing models. This paper proposes a dual-stream sparse Mixer prediction framework that extracts global trends and local dynamic features from sequences in both the frequency and time domains, respectively. It employs a sparsity mechanism to filter out invalid information, thereby enhancing the accuracy of cross-variable dependency modeling. Experimental results demonstrate that this method achieves leading performance on multiple real-world scenario datasets, validating its effectiveness and generality. The code is available at https://github.com/SDMixer/SDMixer
xLSTM-Mixer: Multivariate Time Series Forecasting by Mixing via Scalar Memories
AI & ML Group, TU Darmstadt（AI与机器学习小组，德累斯顿理工大学）；TU Eindhoven（埃因霍温理工大学）；Hessian Center for AI (hessian.AI)（黑森人工智能中心）；German Research Center for AI (DFKI)（德国人工智能研究中心）；Centre for Cognitive Science, TU Darmstadt（认知科学中心，德累斯顿理工大学）
AWEMixer: Adaptive Wavelet-Enhanced Mixer Network for Long-Term Time Series Forecasting
School of Computer Science and Technology, Xi’an Jiaotong University（西安交通大学计算机科学与技术学院）；Department of Research and Development, Shandong New Beiyang Information Technology Co., Ltd.（山东新北洋信息技术有限公司）；Department of Computer Science and Technology, Tsinghua University（清华大学计算机科学与技术学院）
KANMixer: a minimal KAN-centered mixer for long-term time series forecasting
Graduate School of Information Sciences, Tohoku University（东北大学信息科学研究生院）；University of Michigan（密歇根大学）；Worcester Polytechnic Institute（沃思利技术学院）；Texas A&M University（德克萨斯大学）；San Diego State University（圣地亚哥州立大学）
ReLaMix: Residual Latency-Aware Mixing for Delay-Robust Financial Time-Series Forecasting
Lanzhou University（兰州大学）；Brandeis University（品牌斯大学）；Shenzhen University（深圳大学）；Central University of Finance and Economics（中央财经大学）；Central China Normal University（中央师范大学）
ITS-Mina: A Harris Hawks Optimization-Based All-MLP Framework with Iterative Refinement and External Attention for Multivariate Time Series Forecasting
Department of Computer Science and Engineering, Shahid Beheshti University, Iran（伊朗谢赫·贝赫什提大学计算机科学与工程系）；School of Computer Science, Institute for Research in Fundamental Sciences (IPM), Iran（伊朗基础科学研究院（IPM）计算机科学学院）
HieraMix: A Hierarchical MLP-Mixer for Large-Scale Traffic Forecasting
State Key Laboratory of Complex & Critical Software Environment (SKLCCSE)（复杂关键软件环境国家重点实验室）；School of Computer Science and Engineering, Beihang University（北京航空航天大学计算机科学与工程学院）；MOE Engineering Research Center of Advanced Computer Application Technology, Beihang University（教育部先进计算机应用技术工程研究中心，北京航空航天大学）
TS-RAG: Retrieval-Augmented Generation based Time Series Foundation Models are Stronger Zero-Shot Forecaster
School of Computing, University of Connecticut（康奈尔大学计算机学院）；Department of Machine Learning Research, Morgan Stanley（摩根士丹利机器学习研究部）；Ant Group（蚂蚁集团）；TWG Global（TWG全球）
Hybrid Quantum Neural Network for Multivariate Clinical Time Series Forecasting
Department of Diagnostics and Intervention, Radiation Physics, Biomedical Engineering, Umeå University, Sweden（诊断与介入部门，辐射物理，生物医学工程，乌梅大学，瑞典）；Department of Naval, Electrical, Electronics and Telecommunications Engineering, University of Genoa, Italy（海军、电气、电子与电信工程部门，热那亚大学，意大利）
DSO: Dual-Scale Neural Operators for Stable Long-term Fluid Dynamics Forecasting
Institute for Clarity in Documentation（文档清晰度研究所）；Inria Paris-Rocquencourt（法国国家信息与自动化研究所巴黎-罗康库尔）；Rajiv Gandhi University（拉吉夫·甘地大学）；Tsinghua University（清华大学）；Palmer Research Laboratories（帕尔默研究实验室）；University of Science and Technology of China（中国科学技术大学）；Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；Zhejiang University（浙江大学）
SOFTS: Efficient Multivariate Time Series Forecasting with Series-Core Fusion
School of Artificial Intelligence, Nanjing University（南京大学人工智能学院）；National Key Laboratory for Novel Software Technology, Nanjing University（南京大学计算机软件新技术国家重点实验室）
SEMixer: Semantics Enhanced MLP-Mixer for Multiscale Mixing and Long-term Time Series Forecasting
Shanghai Key Laboratory of Data Science, College of Computer Science and Artificial Intelligence Fudan University（上海数据科学 key 实验室，复旦大学计算机科学与人工智能学院）；Harvard University（哈佛大学）
TiRex-2: Generalizing TiRex to Multivariate Data and Streaming
ELLIS Unit Linz, LIT AI Lab & Institute for Machine Learning, JKU Linz, Austria（ELLIS 林茨单元，LIT AI 实验室与机器学习研究所，林茨约翰·开普勒大学，奥地利）；NXAI Lab, Linz, Austria（NXAI 实验室，林茨，奥地利）；NXAI GmbH, Linz, Austria（NXAI 有限公司，林茨，奥地利）；Interdisciplinary Transformation University Austria, Linz, Austria（奥地利跨学科转型大学，林茨，奥地利）
