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Paper page - Patience Is The Key to Large Language Model Reasoning
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Patience is the key in life.

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Papers
arxiv:2411.13082

Patience Is The Key to Large Language Model Reasoning

Published on Nov 20, 2024
· Submitted by
yuyijiong
on Nov 22, 2024
Authors:

Abstract

A method encouraging detailed reasoning in large language models via preference optimization improves performance on complex tasks using a lightweight dataset.

AI-generated summary

Recent advancements in the field of large language models, particularly through the Chain of Thought (CoT) approach, have demonstrated significant improvements in solving complex problems. However, existing models either tend to sacrifice detailed reasoning for brevity due to user preferences, or require extensive and expensive training data to learn complicated reasoning ability, limiting their potential in solving complex tasks. To bridge this gap, following the concept of scaling test-time, we propose a simple method by encouraging models to adopt a more patient reasoning style without the need of introducing new knowledge or skills. To employ a preference optimization approach, we generate detailed reasoning processes as positive examples and simple answers as negative examples, thereby training the model to favor thoroughness in its responses. Our results demonstrate a performance increase of up to 6.7% on GSM8k with training just on a lightweight dataset.

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Paper author Paper submitter
edited Nov 22, 2024

use simple DPO to teach model to reason more patiently
dataset is here

Patience is the key in life.

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