CIKM是CCF B类会议。CIKM 2025将在2025年11月10号到14号在韩国首尔（ Seoul, Korea）举行，本文总结了CIKM2025有关时间序列（Time Series）相关文章，共计24篇，其中1-16为Full Research Paper，17-22为Short Research Paper，23-24为Applied Research Paper。

时间序列Topic：预测，分类，金融时间序列，大模型，基础模型等。如有疏漏，欢迎补充！

Full Research 1. TANDEM: Temporal Attention-guided Neural Differential Equations for Missingness in Time Series Classification 2. Structural Entropy-based Multivariate Time Series Forecasting 3. Frequency-Conditioned Diffusion Models for Time Series Generation 4. EAPformer: Entropy-Aware Patch Transformer for Multivariate Long-Term Time Series Forecasting 5. TableTime: Reformulating Time Series Classification as Training-Free Table Understanding with Large Language Models 6. Multivariate Wind Power Time Series Forecasting with Noise-Filtering Neural ODEs 7. PromptTSS: A Prompting-Based Approach for Interactive Multi-Granularity Time Series Segmentation 8. MSOFormer: Multi-scale Transformer with Orthogonal Embedding and Frequency Modeling for Multivariate Time Series Forecasting 9. MillGNN: Learning Multi-Scale Lead-Lag Dependencies for Multi-Variate Time Series Forecasting 10. Seeing Sequences like Humans: Pattern Classification Driven Time-Series Forecasting via Vision Language Models 11. FinCast: A Foundation Model for Financial Time-Series Forecasting 12. Bidirectional Temporal-Aware Modeling with Multi-Scale Mixture-of-Experts for Multivariate Time Series Forecasting 13. HRCformer: Hierarchical Recursive Convolution-Transformer with Multi-Scale Adaptive Recalibration for Time Series Forecasting 14. WDformer: A Wavelet-Based Differential Transformer Model for Time Series Forecasting 15. AdaPatch: Adaptive Patch-Level Modeling for Non-Stationary Time Series Forecasting 16. TLCCSP: A Scalable Framework for Enhancing Time Series Forecasting with Time-Lagged Cross-Correlations Short Research 17. In-context Pre-trained Time-Series Foundation Models adapt to Unseen Tasks 18. Integrating Time Series into LLMs via Multi-layer Steerable Embedding Fusion for Enhanced Forecasting 19. Modeling Irregular Astronomical Time Series with Neural Stochastic Delay Differential Equations 20. Mixture-of-KAN for Multivariate Time Series Forecasting 21. XDNet: Disentangled Time Series Forecasting via Exponential Decomposition and 2D Periodic Modeling 22. Channel-Independent Refiner for Multivariate Time Series Forecasting Applied Research 23. Dynamic Network-Based Two-Stage Time Series Forecasting for Affiliate Marketing 24. AutoDW-TS: Automated Data Wrangling for Time-Series Data

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Full Research

1 TANDEM: Temporal Attention-guided Neural Differential Equations for Missingness in Time Series Classification

链接：https://arxiv.org/abs/2508.17519

作者：Yongkyung Oh (University of California, Los Angeles(UCLA), United States); , Dongyoung Lim (Ulsan National Institute of Science & Technology(UNIST), South Korea); , Sungil Kim (Ulsan National Institute of Science & Technology(UNIST), South Korea); and Alex Bui (University of California, Los Angeles(UCLA), United States)

关键词：分类，神经差分方程，注意力机制

2 Structural Entropy-based Multivariate Time Series Forecasting

作者：Xinhui Li (School of Information Science and Engineering, Yunnan_x000D_
University, Kunming, China, China); , Kun Yue (School of Information Science and Engineering, Yunnan_x000D_
University, Kunming, China, China); , Lixing Yu (School of Information Science and Engineering, Yunnan_x000D_
University, Kunming, China, China); and Peizhong Yang (School of Information Science and Engineering, Yunnan_x000D_
University, Kunming, China, China)

关键词：多元时间序列预测，熵

3 Frequency-Conditioned Diffusion Models for Time Series Generation

链接：https://openreview.net/forum?id=aIJTNrF2Sg

作者：Seungwoo Jeong (Korea University, South Korea); , Junghyo Sohn (Korea University, South Korea); , Jaehyun Jeon (Korea University, South Korea); and Heung-Il Suk (Korea University, South Korea)

关键词：时间序列生成，扩散模型，傅里叶变换

4 EAPformer: Entropy-Aware Patch Transformer for Multivariate Long-Term Time Series Forecasting

作者：Jiahao Ling (Sun Yat-sen University, China); , Xuan Yang (Sun Yat-sen University, China); , Shimin Gong (Sun Yat-sen University, China); and Bo Gu (Sun Yat-sen University, China)

关键词：长时预测，熵感知

5 TableTime: Reformulating Time Series Classification as Training-Free Table Understanding with Large Language Models

链接：https://arxiv.org/abs/2411.15737

作者：Jiahao Wang (State Key Laboratory of Cognitive Intelligence, University_x000D_
of Science and Technology of China, China); , Mingyue Cheng (State Key Laboratory of Cognitive Intelligence, University_x000D_
of Science and Technology of China, China); , Qingyang Mao (State Key Laboratory of Cognitive Intelligence, University_x000D_
of Science and Technology of China, China); , Yitong Zhou (State Key Laboratory of Cognitive Intelligence, University_x000D_
of Science and Technology of China, China); , Daoyu Wang (State Key Laboratory of Cognitive Intelligence, University_x000D_
of Science and Technology of China, China); , Qi Liu (State Key Laboratory of Cognitive Intelligence, University_x000D_
of Science and Technology of China, China); , Feiyang Xu (Artificial Intelligence Research Institute, iFLYTEK Co.,x000D
Ltd., China); and Xin Li (Artificial Intelligence Research Institute, iFLYTEK Co.,x000D
Ltd., China)

关键词：分类，表格理解，大模型

6 Multivariate Wind Power Time Series Forecasting with Noise-Filtering Neural ODEs

作者：Chang Tianyu (Software engneering, Northeastern University, China); , Dongming Chen (Software engneering, Northeastern University, China); and Dongqi Wang (Software engneering, Northeastern University, China)

关键词：风能预测，神经常微分方程

7 PromptTSS: A Prompting-Based Approach for Interactive Multi-Granularity Time Series Segmentation

链接：https://arxiv.org/abs/2506.11170

作者：Ching Chang (National Yang Ming Chiao Tung University, Taiwan); , Ming-Chih Lo (National Yang Ming Chiao Tung University, Taiwan); , Wen-Chih Peng (National Yang Ming Chiao Tung University, Taiwan); and Tien-Fu Chen (National Yang Ming Chiao Tung University, Taiwan)

关键词：时间序列分割，多粒度

8 MSOFormer: Multi-scale Transformer with Orthogonal Embedding and Frequency Modeling for Multivariate Time Series Forecasting

作者：Qin Shi (China Mobile(Suzhou)Software Technology Co., Ltd, China); , Chu Xu (China Mobile(Suzhou)Software Technology Co., Ltd, China); , Zongtang Hu (China Mobile(Suzhou)Software Technology Co., Ltd, China); , Dong Shen (China Mobile(Suzhou)Software Technology Co., Ltd, China); , Dapeng Sun (China Mobile(Suzhou)Software Technology Co., Ltd, China); and Lijun Quan (Soochow University, Jiangsu, China, China)

关键词：预测，频域建模

9 MillGNN: Learning Multi-Scale Lead-Lag Dependencies for Multi-Variate Time Series Forecasting

链接：https://arxiv.org/abs/2509.03852

作者：Binqing Wu (Zhejiang University, China); , Zongjiang Shang (Zhejiang University, China); , Jianlong Huang (Zhejiang University, China); and Ling Chen (Zhejiang University, China)

关键词：多元时序预测，图神经网络

10 Seeing Sequences like Humans: Pattern Classification Driven Time-Series Forecasting via Vision Language Models

作者：Xingyu Liu (Chongqing University, China); , Min Gao (Chongqing University, China); , Zongwei Wang (Chongqing University, China); and Yinbing Bai (Chongqing University, China)

关键词：预测，视觉语言模型

11 FinCast: A Foundation Model for Financial Time-Series Forecasting

链接：https://arxiv.org/abs/2508.19609

作者：Zhuohang Zhu (The University of Sydney, Australia); , Haodong Chen (The University of Sydney, Australia); , Qiang Qu (The University of Sydney, Australia, Australia); and Vera Chung (The University of Sydney, Australia)

关键词：金融时序基础模型

12 Bidirectional Temporal-Aware Modeling with Multi-Scale Mixture-of-Experts for Multivariate Time Series Forecasting

作者：Yifan Gao (Zhejiang University, China); , Boming Zhao (Zhejiang University, China); , Haocheng Peng (Zhejiang University, China); , Hujun Bao (Zhejiang University, China); , Jiashu Zhao (Wilfrid Laurier University, Canada); and Zhaopeng Cui (Zhejiang University, China)

关键词：多元时序预测，混合专家系统

13 HRCformer: Hierarchical Recursive Convolution-Transformer with Multi-Scale Adaptive Recalibration for Time Series Forecasting

作者：Dejiang Zhang (College of Computer Science and Technology, China University of Petroleum(East China), China, China); , Lianyong Qi (College of Computer Science and Technology, China University of Petroleum(East China), China, China); , Yuwen Liu (College of Computer Science and Technology, China University of Petroleum(East China), China, China); , Xucheng Zhou (College of Computer Science and Technology, China University of Petroleum(East China), China, China); , Jianye Xie (College of Computer Science and Technology, China University of Petroleum(East China), China, China); , Haolong Xiang (School of Software, Nanjing University of Information Science and Technology, China, China); , Xiaolong Xu (School of Software, Nanjing University of Information Science and Technology, China, China); , Xuyun Zhang (Department of Computing, Macquarie University, Australia, Australia); , Yang Cao (School of Computing and Information Technology, Great Bay University, China, China); and Yang Zhang (Anuradha and Vikas Sinha Department of Data Science, University of North Texas, USA, United States)

关键词：预测，卷积，Transformer

14 WDformer: A Wavelet-Based Differential Transformer Model for Time Series Forecasting

作者：Xiaojian Wang (Zhejiang Normal University, China); , Chaoli Zhang (Zhejiang Normal University, China); , Zhonglong Zheng (Zhejiang Normal University, China); and Yunliang Jiang (Zhejiang Normal University, China)

关键词：预测，差分，小波

15 AdaPatch: Adaptive Patch-Level Modeling for Non-Stationary Time Series Forecasting

作者：Kun Liu (East China Normal University, China); , Zhongjie Duan (East China Normal University, China); , Cen Chen (East China Normal University, China); , Yanhao Wang (East China Normal University, China); , Dawei Cheng (Tongji University, China); and Yuqi Liang (Seek Data Group, Emoney Inc., China)

关键词：非平稳时序预测

16 TLCCSP: A Scalable Framework for Enhancing Time Series Forecasting with Time-Lagged Cross-Correlations

链接：https://arxiv.org/abs/2508.07016

作者：Jianfei Wu (Beijing Normal University, China); , Wenmian Yang (Beijing Normal University, China); , Bingning Liu (Beijing Normal University, China); and Weijia Jia (Beijing Normal University, China)

关键词：时间序列预测，时间滞后互相关，对比学习

Short Research

17 In-context Pre-trained Time-Series Foundation Models adapt to Unseen Tasks

链接：https://openreview.net/forum?id=fsth7QcKOd

作者：Shangqing Xu (Georgia Institute of Technology, United States); , Harshavardhan Kamarthi (Georgia Institute of Technology, United States); , Haoxin Liu (Georgia Institute of Technology, United States); and B. Aditya Prakash (Georgia Institute of Technology, United States)

关键词：基础模型，上下文学习

18 Integrating Time Series into LLMs via Multi-layer Steerable Embedding Fusion for Enhanced Forecasting

链接：https://arxiv.org/abs/2508.16059

作者：Zhuomin Chen (Sun Yat-sen University, China); , Dan Li (Sun Yat-sen University, China); , Jiahui Zhou (Sun Yat-sen University, China); , Shunyu Wu (Sun Yat-sen University, China); , Haozheng Ye (Sun Yat-sen University, China); , Jian Lou (Sun Yat-sen University, China); and See-Kiong Ng (National University of Singapore, Singapore)

关键词：预测，大模型，嵌入聚合

19 Modeling Irregular Astronomical Time Series with Neural Stochastic Delay Differential Equations

链接：https://arxiv.org/abs/2508.17521

作者：Yongkyung Oh (University of California, Los Angeles(UCLA), United States); , Seungsu Kam (Ulsan National Institute of Science & Technology(UNIST), South Korea); , Dongyoung Lim (Ulsan National Institute of Science & Technology(UNIST), South Korea); and Sungil Kim (Ulsan National Institute of Science & Technology(UNIST), South Korea)

关键词：分类，神经差分方程

20 Mixture-of-KAN for Multivariate Time Series Forecasting

链接：https://arxiv.org/abs/2408.11306

作者：Xiao Han (University of Chinese Academy of Sciences, China); , Zhenduo Zhang (University of Chinese Academy of Sciences, China); , Xinfeng Zhang (University of Chinese Academy of Sciences, China); , Yiling Wu (Institute of Perceptual Intelligence, Pengcheng Laboratory, China); and Zhe Wu (Institute of Perceptual Intelligence, Pengcheng Laboratory, China)

关键词：预测，KAN

21 XDNet: Disentangled Time Series Forecasting via Exponential Decomposition and 2D Periodic Modeling

作者：Kening Huang (Heilongjiang University, China); , Qianqian Ren (Heilongjiang University, China); and Xingfeng Lv (Heilongjiang University, China)

关键词：预测，指数分解，周期建模

22 Channel-Independent Refiner for Multivariate Time Series Forecasting

作者：Jie Wang (Fujitsu Research and Development Center, China); , Zhongguang Zheng (Fujitsu Research and Development Center, China); , Chaoliang Zhong (Fujitsu Research and Development Center, China); and Jun Sun (Fujitsu Research and Development Center, China)

关键词：预测，通道独立

Applied Research

23 Dynamic Network-Based Two-Stage Time Series Forecasting for Affiliate Marketing

作者：Zhe Wang (Xidian University, China); , Yaming Yang (Xidian University, China); , Ziyu Guan (Xidian University, China); , Bin Tong (Alibaba Group, China); , Rui Wang (Alibaba Group, China); , Wei Zhao (Xidian University, China); and Hongbo Deng (Alibaba Group, China)

关键词：预测，电商

24 AutoDW-TS: Automated Data Wrangling for Time-Series Data

作者：Lei Liu (Fujitsu Research of America Inc., United States); , So Hasegawa (Fujitsu Research of America Inc., United States); , Shailaja Keyur Sampat (Fujitsu Research of America Inc., United States); , Mehdi Bahrami (Fujitsu Research of America Inc., United States); , Wei-Peng Chen (Fujitsu Research of America Inc., United States); , Kodai Toyota (Fujitsu Research, Japan); , Takashi Kato (Fujitsu Research, Japan); , Takumi Akazaki (Fujitsu Research, Japan); , Akira Ura (Fujitsu Research, Japan); and Tatsuya Asai (Fujitsu Research, Japan)

关键词：时序数据整理

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