GAMMT: Generative Ambiguity Modeling Using Multiple Transformers. - Xingcheng Xu (CoRR, 2022)

Deep Generative Modeling with Backward Stochastic Differential Equations. - Xingcheng Xu (CoRR, 2023)

Large Language Models at Work in China's Labor Market. - Qin Chen; Jinfeng Ge; Huaqing Xie; Xingcheng Xu; Yanqing Yang (CoRR, 2023)

It Ain't That Bad: Understanding the Mysterious Performance Drop in OOD Generalization for Generative Transformer Models. - Xingcheng Xu; Zihao Pan; Haipeng Zhang; Yanqing Yang (IJCAI, 2024)

Machine Learning for Economic Forecasting: An Application to China's GDP Growth. - Yanqing Yang; Xingcheng Xu; Jinfeng Ge; Yan Xu (CoRR, 2024)

Optimal Trade and Industrial Policies in the Global Economy: A Deep Learning Framework. - Zi Wang; Xingcheng Xu; Yanqing Yang; Xiaodong Zhu (CoRR, 2024)

Relating the Seemingly Unrelated: Principled Understanding of Generalization for Generative Models in Arithmetic Reasoning Tasks. - Xingcheng Xu; Zibo Zhao; Haipeng Zhang; Yanqing Yang (CoRR, 2024)

Principled Understanding of Generalization for Generative Transformer Models in Arithmetic Reasoning Tasks. - Xingcheng Xu; Zibo Zhao; Haipeng Zhang; Yanqing Yang (ACL (1), 2025)

DeepInnovation AI: A Global Dataset Mapping the AI innovation from Academic Research to Industrial Patents. - Haixing Gong; Zou Hui; Liang Xingzhou; Shiyuan Meng; Pinlong Cai; Xingcheng Xu; Jingjing Qu (CoRR, 2025)

SafeWork-R1: Coevolving Safety and Intelligence under the AI-45° Law. - Yicheng Bao; Guanxu Chen; Mingkang Chen; Yunhao Chen; Chiyu Chen; Lingjie Chen; Sirui Chen; Xinquan Chen; Jie Cheng; Yu Cheng 001; Dengke Deng; Yizhuo Ding; et al. (CoRR, 2025)

The Policy Cliff: A Theoretical Analysis of Reward-Policy Maps in Large Language Models. - Xingcheng Xu (CoRR, 2025)