REL: Working out is all you need

• URL: http://arxiv.org/abs/2412.04645v1
• Date: Thu, 05 Dec 2024 22:32:01 GMT
• Title: REL: Working out is all you need
• Authors: Toby Simonds, Jey Han Lau, Chaithanya Bandi,
• Abstract summary: We observe that OpenAI's O1 model approaches problem-solving in a distinctly human-like manner. These sophisticated reasoning capabilities remain notably absent in other state-of-the-art language models.
• Score: 20.65423513616306
• License:
• Abstract: Recent developments, particularly OpenAI's O1 model, have demonstrated the remarkable potential of Large Language Models (LLMs) for complex reasoning tasks. Through analysis of O1's outputs and provided sample Chain-of-Thought (CoT) demonstrations, we observe that it approaches problem-solving in a distinctly human-like manner, systematically brainstorming ideas, testing hypotheses, verifying results, and planning comprehensive solutions. These sophisticated reasoning capabilities remain notably absent in other state-of-the-art language models. In this paper, we hypothesize that this performance gap stems from the limited availability of high-quality reasoning process data in current training sets. We demonstrate that by constructing a specialized dataset focused on explicit problem-solving workflows ("worked solutions"), we can elicit substantially improved planning capabilities from existing models. Additionally, we propose the Reasoning Enhancement Loop (REL), a method for generating synthetic worked solutions.

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