Jian Xu

According to our database, Jian Xu authored at least 31 papers between 2021 and 2026.

Collaborative distances:

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

2026

FactorMiner: A Self-Evolving Agent with Skills and Experience Memory for Financial Alpha Discovery.

Yanlong Wang, Jian Xu, Hongkang Zhang, Shao-Lun Huang, Danny Dongning Sun, Xiao-Ping Zhang

CoRR, February, 2026

Integrating Large Language Models Into Recommendation via Mutual Augmentation and Adaptive Aggregation.

Sichun Luo, Yuxuan Yao, Bowei He, Wei Shao, Jian Xu, Yinya Huang, Aojun Zhou, Xinyi Zhang, Yuanzhang Xiao, Hanxu Hou, Mingjie Zhan, Linqi Song

IEEE J. Sel. Top. Signal Process., January, 2026

VFEM: Visual Feature Empowered Multivariate Time Series Forecasting with Cross-Modal Fusion.

Yanlong Wang, Hang Yu, Jian Xu, Fei Ma, Hongkang Zhang, Tongtong Feng, Zijian Zhang, Shao-Lun Huang, Danny Dongning Sun, Xiao-Ping Zhang

Trans. Mach. Learn. Res., 2026

RALLRec+: Retrieval augmented large language model recommendation with reasoning.

Sichun Luo, Jian Xu, Xiaojie Zhang, Linrong Wang, Sicong Liu, Hanxu Hou, Linqi Song

Expert Syst. Appl., 2026

2025

VIFO: Visual Feature Empowered Multivariate Time Series Forecasting with Cross-Modal Fusion.

Yanlong Wang, Hang Yu, Jian Xu, Fei Ma, Hongkang Zhang, Tongtong Feng, Zijian Zhang, Shao-Lun Huang, Danny Dongning Sun, Xiao-Ping Zhang

CoRR, October, 2025

FinZero: Launching Multi-modal Financial Time Series Forecast with Large Reasoning Model.

Yanlong Wang, Jian Xu, Fei Ma, Hongkang Zhang, Hang Yu, Tiantian Gao, Yu Wang, Haochen You, Shao-Lun Huang, Danny Dongning Sun, Xiao-Ping Zhang

CoRR, September, 2025

Reasoning Meets Personalization: Unleashing the Potential of Large Reasoning Model for Personalized Generation.

Sichun Luo, Guanzhi Deng, Jian Xu, Xiaojie Zhang, Hanxu Hou, Linqi Song

CoRR, May, 2025

Assessing Uncertainty in Stock Returns: A Gaussian Mixture Distribution-Based Method.

Yanlong Wang, Jian Xu, Shao-Lun Huang, Danny Dongning Sun, Xiao-Ping Zhang

CoRR, March, 2025

FinTSBridge: A New Evaluation Suite for Real-world Financial Prediction with Advanced Time Series Models.

Yanlong Wang, Jian Xu, Tiantian Gao, Hongkang Zhang, Shao-Lun Huang, Danny Dongning Sun, Xiao-Ping Zhang

CoRR, March, 2025

Stabilizing and improving federated learning with highly non-iid data and client dropout.

Jian Xu, Meilin Yang, Wenbo Ding, Shao-Lun Huang

Appl. Intell., February, 2025

Cooperative Multi-Model Training for Personalized Federated Learning Over Heterogeneous Devices.

Jian Xu, Shuo Wan, Yinchuan Li, Sichun Luo, Zhilin Chen, Yunfeng Shao, Zhitang Chen, Shao-Lun Huang, Linqi Song

IEEE J. Sel. Top. Signal Process., January, 2025

RALLRec: Improving Retrieval Augmented Large Language Model Recommendation with Representation Learning.

Jian Xu, Sichun Luo, Xiangyu Chen, Haoming Huang, Hanxu Hou, Linqi Song

Proceedings of the Companion Proceedings of the ACM on Web Conference 2025, 2025

Transferability Prediction for Model Recommendation: A Graph Learning Method.

Xiangyu Chen, Yanru Wu, Jian Xu, Wenhao Guo, Yang Li, Xiaoping Zhang

Proceedings of the IEEE Conference on Artificial Intelligence, 2025

pFedGPA: Diffusion-based Generative Parameter Aggregation for Personalized Federated Learning.

Jiahao Lai, Jiaqi Li, Jian Xu, Yanru Wu, Boshi Tang, Siqi Chen, Yongfeng Huang, Wenbo Ding, Yang Li

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

FedHAP: Federated Hashing With Global Prototypes for Cross-Silo Retrieval.

Meilin Yang, Jian Xu, Wenbo Ding, Yang Liu

IEEE Trans. Parallel Distributed Syst., April, 2024

On the Fundamental Limit of Distributed Learning With Interchangable Constrained Statistics.

Xinyi Tong, Jian Xu, Shao-Lun Huang

IEEE J. Sel. Areas Inf. Theory, 2024

PSformer: Parameter-efficient Transformer with Segment Attention for Time Series Forecasting.

Yanlong Wang, Jian Xu, Fei Ma, Shao-Lun Huang, Danny Dongning Sun, Xiao-Ping Zhang

CoRR, 2024

Privacy in LLM-based Recommendation: Recent Advances and Future Directions.

Sichun Luo, Wei Shao, Yuxuan Yao, Jian Xu, Mingyang Liu, Qintong Li, Bowei He, Maolin Wang, Guanzhi Deng, Hanxu Hou, Xinyi Zhang, Linqi Song

CoRR, 2024

NAC: Mitigating Noisy Correspondence in Cross-Modal Matching Via Neighbor Auxiliary Corrector.

Yuqing Li, Haoming Huang, Jian Xu, Shao-Lun Huang

Proceedings of the IEEE International Conference on Acoustics, 2024

2023

Stabilizing and Improving Federated Learning with Non-IID Data and Client Dropout.

Jian Xu, Meiling Yang, Wenbo Ding, Shao-Lun Huang

CoRR, 2023

Mitigating Model Poisoning Attacks on Distributed Learning with Heterogeneous Data.

Jian Xu, Guangfeng Yan, Ziyan Zheng, Shao-Lun Huang

Proceedings of the International Conference on Machine Learning and Applications, 2023

Personalized Federated Learning with Feature Alignment and Classifier Collaboration.

Jian Xu, Xinyi Tong, Shao-Lun Huang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

A Joint Training-Calibration Framework for Test-Time Personalization with Label Shift in Federated Learning.

Jian Xu, Shao-Lun Huang

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022

An Information-theoretic Method for Collaborative Distributed Learning with Limited Communication.

Xinyi Tong, Jian Xu, Shao-Lun Huang

Proceedings of the IEEE Information Theory Workshop, 2022

FedPer++: Toward Improved Personalized Federated Learning on Heterogeneous and Imbalanced Data.

Jian Xu, Yi Yan, Shao-Lun Huang

Proceedings of the International Joint Conference on Neural Networks, 2022

Byzantine-robust Federated Learning through Collaborative Malicious Gradient Filtering.

Jian Xu, Shao-Lun Huang, Linqi Song, Tian Lan

Proceedings of the 42nd IEEE International Conference on Distributed Computing Systems, 2022

Communication-Efficient and Byzantine-Robust Distributed Stochastic Learning with Arbitrary Number of Corrupted Workers.

Jian Xu, Xinyi Tong, Shao-Lun Huang

Proceedings of the IEEE International Conference on Communications, 2022

Byzantine-Resilient Decentralized Collaborative Learning.

Jian Xu, Shao-Lun Huang

Proceedings of the IEEE International Conference on Acoustics, 2022

Federated Capsule Graph Neural Network with Personalization.

Meilin Yang, Jian Xu, Wenbo Ding, Yang Liu

Proceedings of the Adjunct Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2022 ACM International Symposium on Wearable Computers, 2022

2021

SignGuard: Byzantine-robust Federated Learning through Collaborative Malicious Gradient Filtering.

Jian Xu, Shao-Lun Huang, Linqi Song, Tian Lan

CoRR, 2021

Live Gradient Compensation for Evading Stragglers in Distributed Learning.

Jian Xu, Shao-Lun Huang, Linqi Song, Tian Lan

Proceedings of the 40th IEEE Conference on Computer Communications, 2021