Shing-Tung Yau — accepted AI-conference papers

2026

Editable Proof Sketch for Automated Theorem Proving

Zikai Xiao, Hanzheng Wang, Meng-Hao Guo, Shi-min Hu, Shing-Tung Yau

ICML 2026poster

As large language models (LLMs) improve in mathematical reasoning and formal understanding, a promising approach for automated theorem proving (ATP) is to enable LLMs construct proof sketches, which plan a high-level proof strategy and decompose complex theorems into independently provable subgoals.…

Cited by 0 Source ↗Scholar ↗

2020

AE-OT: A NEW GENERATIVE MODEL BASED ON EXTENDED SEMI-DISCRETE OPTIMAL TRANSPORT

Dongsheng An, Yang Guo, Na Lei, Zhongxuan Luo, Shing-Tung Yau, Xianfeng Gu

ICLR 2020poster

Generative adversarial networks (GANs) have attracted huge attention due to its capability to generate visual realistic images. However, most of the existing models suffer from the mode collapse or mode mixture problems. In this work, we give a theoretic explanation of the both problems by Figalli’s…

Cited by 65 Source ↗Scholar ↗