Yankai Shu — accepted AI-conference papers

2026

Investigating Advanced Reasoning of Large Language Models via Black-Box Interaction

Congchi Yin, Tianyi Wu, Yankai Shu, Alex Gu, Yun Wang, Jun Shao +2

ICML 2026poster

Existing tasks fall short in evaluating reasoning ability of Large Language Models (LLMs) in an interactive, unknown environment. This deficiency leads to the isolated assessment of deductive, inductive, and abductive reasoning, neglecting the integrated reasoning process that is indispensable for h…

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2026

Towards Solving the Gilbert-Pollak Conjecture via Large Language Models

Yisi Ke, Tianyu Huang, Yankai Shu, Di He, Jingchu Gai, Liwei Wang

ICML 2026poster

The Gilbert-Pollak Conjecture, also known as the Steiner Ratio Conjecture, states that for any finite point set in the Euclidean plane, the Steiner minimum tree has length at least $\sqrt{3}/2 \approx 0.866$ times that of the Euclidean minimum spanning tree (the Steiner ratio). A sequence of improve…

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