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Unlocking Reasoning Potential in Large Language Models by Scaling Code-form Planning

This repository contains the dataset for our paper:

Unlocking Reasoning Potential in Large Language Models by Scaling Code-form Planning

In this work, we introduce CodePlan, a scalable framework that empowers LLMs to generate and follow code-form plans---pseudocode that outlines high-level, structured reasoning processes.

By leveraing the structured and versatile nature of code, CodePlan effectively captures the rich semantics and control flows inherent to sophisticated reasoning tasks.

Dataset

huggingface dataset: link

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