A General Distributed Dual Coordinate Optimization Framework for Regularized Loss Minimization. - Shun Zheng 001; Fen Xia; Wei Xu 005; Tong Zhang 001 (CoRR, 2016)

A General Distributed Dual Coordinate Optimization Framework for Regularized Loss Minimization. - Shun Zheng 001; Jialei Wang; Fen Xia; Wei Xu 005; Tong Zhang 001 (J. Mach. Learn. Res., 2017)

DIAG-NRE: A Deep Pattern Diagnosis Framework for Distant Supervision Neural Relation Extraction. - Shun Zheng 001; Peilin Yu; Lu Chen; Ling Huang 001; Wei Xu 005 (CoRR, 2018)

DIAG-NRE: A Neural Pattern Diagnosis Framework for Distantly Supervised Neural Relation Extraction. - Shun Zheng 001; Xu Han 007; Yankai Lin; Peilin Yu; Lu Chen; Ling Huang 001; Zhiyuan Liu 001; Wei Xu 005 (ACL (1), 2019)

Doc2EDAG: An End-to-End Document-level Framework for Chinese Financial Event Extraction. - Shun Zheng 001; Wei Cao 007; Wei Xu 005; Jiang Bian 002 (EMNLP/IJCNLP (1), 2019)

SEEK: Segmented Embedding of Knowledge Graphs. - Wentao Xu; Shun Zheng 001; Liang He 010; Bin Shao; Jian Yin 001; Tie-Yan Liu (ACL, 2020)

Revisiting the Evaluation of End-to-end Event Extraction. - Shun Zheng 001; Wei Cao 007; Wei Xu 005; Jiang Bian 002 (ACL/IJCNLP (Findings), 2021)

HierST: A Unified Hierarchical Spatial-temporal Framework for COVID-19 Trend Forecasting. - Shun Zheng 001; Zhifeng Gao; Wei Cao 007; Jiang Bian 002; Tie-Yan Liu (CIKM, 2021)

The CityLearn Challenge 2022: Overview, Results, and Lessons Learned. - Kingsley Nweye; Zoltán Nagy 002; Sharada P. Mohanty; Dipam Chakraborty; Siva Sankaranarayanan; Tianzhen Hong; Sourav Dey; Gregor Henze; Ján Drgona; Fangquan Lin; Wei Jiang 027; Hanwei Zhang 002; et al. (NeurIPS (Competition and Demos), 2021)

A continuous glucose monitoring measurements forecasting approach via sporadic blood glucose monitoring. - Yuting Xing; Hangting Ye; Xiaoyu Zhang 008; Wei Cao 007; Shun Zheng 001; Jiang Bian 002; Yike Guo (BIBM, 2022)

A Graph-based Spatiotemporal Model for Energy Markets. - Swati Sharma; Srinivasan Iyengar; Shun Zheng 001; Kshitij Kapoor; Wei Cao 007; Jiang Bian 002; Shivkumar Kalyanaraman; John Lemmon (CIKM, 2022)

DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting. - Wei Fan 010; Shun Zheng 001; Xiaohan Yi; Wei Cao 007; Yanjie Fu; Jiang Bian 002; Tie-Yan Liu (ICLR, 2022)

Learning Differential Operators for Interpretable Time Series Modeling. - Yingtao Luo; Chang Xu 008; Yang Liu 278; Weiqing Liu; Shun Zheng 001; Jiang Bian 002 (KDD, 2022)

Efficient and Effective Multi-task Grouping via Meta Learning on Task Combinations. - Xiaozhuang Song; Shun Zheng 001; Wei Cao 007; James J. Q. Yu; Jiang Bian 002 (NeurIPS, 2022)

Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures. - Tianping Zhang; Yizhuo Zhang 001; Wei Cao 007; Jiang Bian 002; Xiaohan Yi; Shun Zheng 001; Jian Li 015 (CoRR, 2022)

UADB: Unsupervised Anomaly Detection Booster. - Hangting Ye; Zhining Liu 002; Xinyi Shen; Wei Cao 007; Shun Zheng 001; Xiaofan Gui; Huishuai Zhang; Yi Chang 001; Jiang Bian 002 (ICDE, 2023)

Warpformer: A Multi-scale Modeling Approach for Irregular Clinical Time Series. - Jiawen Zhang 001; Shun Zheng 001; Wei Cao 007; Jiang Bian 002; Jia Li 009 (KDD, 2023)

Learning Intra- and Inter-Cell Differences for Accurate Battery Lifespan Prediction across Diverse Conditions. - Han Zhang; Yuqi Li; Shun Zheng 001; Ziheng Lu; Xiaofan Gui; Wei Xu 005; Jiang Bian 002 (CoRR, 2023)

Towards Foundation Models for Learning on Tabular Data. - Han Zhang; Xumeng Wen; Shun Zheng 001; Wei Xu 005; Jiang Bian 002 (CoRR, 2023)

ProbTS: A Unified Toolkit to Probe Deep Time-series Forecasting. - Jiawen Zhang 001; Xumeng Wen; Shun Zheng 001; Jia Li 009; Jiang Bian 002 (CoRR, 2023)

PTaRL: Prototype-based Tabular Representation Learning via Space Calibration. - Hangting Ye; Wei Fan 010; Xiaozhuang Song; Shun Zheng 001; He Zhao 001; Dandan Guo; Yi Chang 001 (ICLR, 2024)

BatteryML: An Open-source Platform for Machine Learning on Battery Degradation. - Han Zhang; Xiaofan Gui; Shun Zheng 001; Ziheng Lu; Yuqi Li; Jiang Bian 002 (ICLR, 2024)

From Supervised to Generative: A Novel Paradigm for Tabular Deep Learning with Large Language Models. - Xumeng Wen; Han Zhang; Shun Zheng 001; Wei Xu 005; Jiang Bian 002 (KDD, 2024)

ProbTS: Benchmarking Point and Distributional Forecasting across Diverse Prediction Horizons. - Jiawen Zhang 001; Xumeng Wen; Zhenwei Zhang; Shun Zheng 001; Jia Li 009; Jiang Bian 002 (NeurIPS, 2024)

ElasTST: Towards Robust Varied-Horizon Forecasting with Elastic Time-Series Transformer. - Jiawen Zhang 001; Shun Zheng 001; Xumeng Wen; Xiaofang Zhou; Jiang Bian 002; Jia Li 009 (NeurIPS, 2024)

Addressing Distribution Shift in Time Series Forecasting with Instance Normalization Flows. - Wei Fan 010; Shun Zheng 001; Pengyang Wang; Rui Xie 002; Jiang Bian 002; Yanjie Fu (CoRR, 2024)

Large Language Model as a Universal Clinical Multi-task Decoder. - Yujiang Wu; Hongjian Song; Jiawen Zhang 001; Xumeng Wen; Shun Zheng 001; Jiang Bian 002 (CoRR, 2024)

Challenges of COVID-19 Case Forecasting in the US, 2020-2021. - Velma K. Lopez; Estee Y. Cramer; Robert Pagano; John M. Drake; Eamon B. O'Dea; Madeline Adee; Turgay Ayer; Jagpreet Chhatwal; Ozden O. Dalgic; Mary A. Ladd; Benjamin P. Linas; Peter P. Mueller; et al. (PLoS Comput. Biol., 2024)

DEWP: Deep Expansion Learning for Wind Power Forecasting. - Wei Fan 010; Yanjie Fu; Shun Zheng 001; Jiang Bian 002; Yuanchun Zhou; Hui Xiong 001 (ACM Trans. Knowl. Discov. Data, 2024)

IN-Flow: Instance Normalization Flow for Non-stationary Time Series Forecasting. - Wei Fan 010; Shun Zheng 001; Pengyang Wang; Rui Xie 002; Kun Yi 001; Qi Zhang 020; Jiang Bian 002; Yanjie Fu (KDD (1), 2025)

Battery lifetime prediction across diverse ageing conditions with inter-cell deep learning. - Han Zhang; Yuqi Li; Shun Zheng 001; Ziheng Lu; Xiaofan Gui; Wei Xu 005; Jiang Bian 002 (Nat. Mac. Intell., 2025)

Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models. - Xumeng Wen; Shun Zheng 001; Zhen Xu; Yiming Sun 004; Jiang Bian 002 (CoRR, 2025)

Chemistry-aware battery degradation prediction under simulated real-world cyclic protocols. - Yuqi Li; Han Zhang; Xiaofan Gui; Zhao Chen; Yu Li; Xiwen Chi; Quan Zhou; Shun Zheng 001; Ziheng Lu; Wei Xu 005; Jiang Bian 002; Liquan Chen; et al. (CoRR, 2025)

Are Time-Series Foundation Models Deployment-Ready? A Systematic Study of Adversarial Robustness Across Domains. - Jiawen Zhang 001; Zhenwei Zhang; Shun Zheng 001; Xumeng Wen; Jia Li 009; Jiang Bian 002 (CoRR, 2025)

Reinforcement Learning with Verifiable Rewards Implicitly Incentivizes Correct Reasoning in Base LLMs. - Xumeng Wen; Zihan Liu; Shun Zheng 001; Zhijian Xu; Shengyu Ye; Zhirong Wu; Xiao Liang; Yang Wang 053; Junjie Li; Ziming Miao; Jiang Bian 002; Mao Yang 004 (CoRR, 2025)