Xiangfei Qiu

According to our database, Xiangfei Qiu authored at least 31 papers between 2024 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Differentiable Mixture-of-Agents Incentivizes Swarm Intelligence of Large Language Models.

Xingjian Wu, Junkai Lu, Siyu Yan, Xiangfei Qiu, Jilin Hu, Chenjuan Guo, Bin Yang

CoRR, May, 2026

GCGNet: Graph-Consistent Generative Network for Time Series Forecasting with Exogenous Variables.

Zhengyu Li, Xiangfei Qiu, Yuhan Zhu, Xingjian Wu, Jilin Hu, Chenjuan Guo, Bin Yang

CoRR, March, 2026

ST-EVO: Towards Generative Spatio-Temporal Evolution of Multi-Agent Communication Topologies.

Xingjian Wu, Xvyuan Liu, Junkai Lu, Siyuan Wang, Xiangfei Qiu, Yang Shu, Jilin Hu, Chenjuan Guo, Bin Yang

CoRR, February, 2026

MEMTS: Internalizing Domain Knowledge via Parameterized Memory for Retrieval-Free Domain Adaptation of Time Series Foundation Models.

Xiaoyun Yu, Li fan, Xiangfei Qiu, Nanqing Dong, Yonggui Huang, Honggang Qi, Geguang Pu, Wanli Ouyang, Xi Chen, Jilin Hu

CoRR, February, 2026

LightGTS-Cov: Covariate-Enhanced Time Series Forecasting.

Yong Shang, Zhipeng Yao, Ning Jin, Xiangfei Qiu, Hui Zhang, Bin Yang

CoRR, February, 2026

SEER: Transformer-based Robust Time Series Forecasting via Automated Patch Enhancement and Replacement.

Xiangfei Qiu, Xvyuan Liu, Tianen Shen, Xingjian Wu, Hanyin Cheng, Bin Yang, Jilin Hu

CoRR, February, 2026

Bridging Time and Frequency: A Joint Modeling Framework for Irregular Multivariate Time Series Forecasting.

Xiangfei Qiu, Kangjia Yan, Xvyuan Liu, Xingjian Wu, Jilin Hu

CoRR, February, 2026

TimeART: Towards Agentic Time Series Reasoning via Tool-Augmentation.

Xingjian Wu, Junkai Lu, Zhe Li, Xiangfei Qiu, Jilin Hu, Chenjuan Guo, Christian S. Jensen, Bin Yang

CoRR, January, 2026

Rethinking Irregular Time Series Forecasting: A Simple Yet Effective Baseline.

Xvyuan Liu, Xiangfei Qiu, Xingjian Wu, Zhengyu Li, Chenjuan Guo, Jilin Hu, Bin Yang

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

FLAME: Flow Enhanced Legendre Memory Models for General Time Series Forecasting.

Xingjian Wu, Hanyin Cheng, Xiangfei Qiu, Zhengyu Li, Jilin Hu, Chenjuan Guo, Bin Yang

CoRR, December, 2025

DBLoss: Decomposition-based Loss Function for Time Series Forecasting.

Xiangfei Qiu, Xingjian Wu, Hanyin Cheng, Xvyuan Liu, Chenjuan Guo, Jilin Hu, Bin Yang

CoRR, October, 2025

An Encode-then-Decompose Approach to Unsupervised Time Series Anomaly Detection on Contaminated Training Data-Extended Version.

Buang Zhang, Tung Kieu, Xiangfei Qiu, Chenjuan Guo, Jilin Hu, Aoying Zhou, Christian S. Jensen, Bin Yang

CoRR, October, 2025

Enhancing Time Series Forecasting through Selective Representation Spaces: A Patch Perspective.

Xingjian Wu, Xiangfei Qiu, Hanyin Cheng, Zhengyu Li, Jilin Hu, Chenjuan Guo, Bin Yang

CoRR, October, 2025

Multi-Scale Spatial-Temporal Hypergraph Network with Lead-Lag Structures for Stock Time Series Forecasting.

Xiangfei Qiu, Liu Yang, Hanyin Cheng, Xingjian Wu, Rongjia Wu, Zhigang Zhang, Ding Tu, Chenjuan Guo, Bin Yang, Christian S. Jensen, Jilin Hu

CoRR, September, 2025

ASTGI: Adaptive Spatio-Temporal Graph Interactions for Irregular Multivariate Time Series Forecasting.

Xvyuan Liu, Xiangfei Qiu, Hanyin Cheng, Xingjian Wu, Chenjuan Guo, Bin Yang, Jilin Hu

CoRR, September, 2025

Unlocking the Power of Mixture-of-Experts for Task-Aware Time Series Analytics.

Xingjian Wu, Zhengyu Li, Hanyin Cheng, Xiangfei Qiu, Jilin Hu, Chenjuan Guo, Bin Yang

CoRR, September, 2025

DAG: A Dual Causal Network for Time Series Forecasting with Exogenous Variables.

Xiangfei Qiu, Yuhan Zhu, Zhengyu Li, Hanyin Cheng, Xingjian Wu, Chenjuan Guo, Bin Yang, Jilin Hu

CoRR, September, 2025

TAB: Unified Benchmarking of Time Series Anomaly Detection Methods.

Xiangfei Qiu, Zhe Li, Wanghui Qiu, Shiyan Hu, Lekui Zhou, Xingjian Wu, Zhengyu Li, Chenjuan Guo, Aoying Zhou, Zhenli Sheng, Jilin Hu, Christian S. Jensen, Bin Yang

Proc. VLDB Endow., May, 2025

K²VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting.

Xingjian Wu, Xiangfei Qiu, Hongfan Gao, Jilin Hu, Bin Yang, Chenjuan Guo

CoRR, May, 2025

A Comprehensive Survey of Deep Learning for Multivariate Time Series Forecasting: A Channel Strategy Perspective.

Xiangfei Qiu, Hanyin Cheng, Xingjian Wu, Jilin Hu, Chenjuan Guo

CoRR, February, 2025

DUET: Dual Clustering Enhanced Multivariate Time Series Forecasting.

Xiangfei Qiu, Xingjian Wu, Yan Lin, Chenjuan Guo, Jilin Hu, Bin Yang

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.1, 2025

SSD-TS: Exploring the Potential of Linear State Space Models for Diffusion Models in Time Series Imputation.

Hongfan Gao, Wangmeng Shen, Xiangfei Qiu, Ronghui Xu, Bin Yang, Jilin Hu

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 2025

TSFM-Bench: A Comprehensive and Unified Benchmark of Foundation Models for Time Series Forecasting.

Zhe Li, Xiangfei Qiu, Peng Chen, Yihang Wang, Hanyin Cheng, Yang Shu, Jilin Hu, Chenjuan Guo, Aoying Zhou, Christian S. Jensen, Bin Yang

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 2025

K2VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting.

Xingjian Wu, Xiangfei Qiu, Hongfan Gao, Jilin Hu, Bin Yang, Chenjuan Guo

Proceedings of the Forty-second International Conference on Machine Learning, 2025

CATCH: Channel-Aware Multivariate Time Series Anomaly Detection via Frequency Patching.

Xingjian Wu, Xiangfei Qiu, Zhengyu Li, Yihang Wang, Jilin Hu, Chenjuan Guo, Hui Xiong, Bin Yang

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

EasyTime: Time Series Forecasting Made Easy.

Xiangfei Qiu, Xiuwen Li, Ruiyang Pang, Zhicheng Pan, Xingjian Wu, Liu Yang, Jilin Hu, Yang Shu, Xuesong Lu, Chengcheng Yang, Chenjuan Guo, Aoying Zhou, Christian S. Jensen, Bin Yang

Proceedings of the 41st IEEE International Conference on Data Engineering, 2025

2024

AutoCTS++: zero-shot joint neural architecture and hyperparameter search for correlated time series forecasting.

Xinle Wu, Xingjian Wu, Bin Yang, Lekui Zhou, Chenjuan Guo, Xiangfei Qiu, Jilin Hu, Zhenli Sheng, Christian S. Jensen

VLDB J., September, 2024

TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods.

Xiangfei Qiu, Jilin Hu, Lekui Zhou, Xingjian Wu, Junyang Du, Buang Zhang, Chenjuan Guo, Aoying Zhou, Christian S. Jensen, Zhenli Sheng, Bin Yang

Proc. VLDB Endow., May, 2024

MultiRC: Joint Learning for Time Series Anomaly Prediction and Detection with Multi-scale Reconstructive Contrast.

Shiyan Hu, Kai Zhao, Xiangfei Qiu, Yang Shu, Jilin Hu, Bin Yang, Chenjuan Guo

CoRR, 2024

DiffImp: Efficient Diffusion Model for Probabilistic Time Series Imputation with Bidirectional Mamba Backbone.

Hongfan Gao, Wangmeng Shen, Xiangfei Qiu, Ronghui Xu, Jilin Hu, Bin Yang

CoRR, 2024

FoundTS: Comprehensive and Unified Benchmarking of Foundation Models for Time Series Forecasting.

Zhe Li, Xiangfei Qiu, Peng Chen, Yihang Wang, Hanyin Cheng, Yang Shu, Jilin Hu, Chenjuan Guo, Aoying Zhou, Qingsong Wen, Christian S. Jensen, Bin Yang

CoRR, 2024