Yuzhe Cai — accepted AI-conference papers

2025

ALYMPICS: LLM Agents Meet Game Theory

Shaoguang Mao, Yuzhe Cai, Yan Xia, Wenshan Wu, Xun Wang, Fengyi Wang +3

COLING 2025main

Game theory is a branch of mathematics that studies strategic interactions among rational agents. We propose Alympics (Olympics for Agents), a systematic framework utilizing Large Language Model (LLM) agents for empirical game theory research. Alympics creates a versatile platform for studying compl…

Cited by 3 Source ↗PDF ↗Scholar ↗

2024

Low-code LLM: Graphical User Interface over Large Language Models

Yuzhe Cai, Shaoguang Mao, Wenshan Wu, Zehua Wang, Yaobo Liang, Tao Ge +6

NAACL 2024system demonstrations

Utilizing Large Language Models (LLMs) for complex tasks is challenging, often involving a time-consuming and uncontrollable prompt engineering process. This paper introduces a novel human-LLM interaction framework, Low-code LLM. It incorporates six types of simple low-code visual programming intera…

Cited by 17 Source ↗PDF ↗code ↗Scholar ↗