Poster
in
Workshop: AI for Math Workshop
Technical Report for ICML 2024 Automated Math Reasoning Challenge: Solving Optimization Problems with Open Source Large Language Model
Duc M. Nguyen · Sungahn Ko
Abstract:
This technical report presents an approach utilizing open-source Large Language Models for Automated Optimization Problem-solving With Code Challenge at the ICML 2024 AI4Math Workshop. This challenge emphasizes the ability of Large Language Models (LLMs) to handle complex mathematical reasoning from formulating to solving the problem at hand. By exploring different prompting techniques, such as few-shot, self-consistency, chain-of-thought, and tree-of-thought, we aim to explore the current state-of-the-art LLMs' mathematical reasoning abilities.
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