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)

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)

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)

NuTime: Numerically Multi-Scaled Embedding for Large- Scale Time-Series Pretraining. - Chenguo Lin; Xumeng Wen; Wei Cao 007; Congrui Huang; Jiang Bian 002; Stephen Lin 001; Zhirong Wu (Trans. Mach. Learn. Res., 2024)

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)

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)