Summary of Rel: Working Out Is All You Need, by Toby Simonds et al.
REL: Working out is all you need
by Toby Simonds, Jey Han Lau, Chaithanya Bandi
First submitted to arxiv on: 5 Dec 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Recent advancements in Large Language Models (LLMs) have shown impressive potential for complex reasoning tasks, particularly with OpenAI’s O1 model. Analyzing O1’s outputs and provided Chain-of-Thought (CoT) demonstrations reveals a human-like approach to problem-solving, involving systematic idea generation, hypothesis testing, result verification, and comprehensive solution planning. This sophisticated reasoning capability is distinct from other state-of-the-art language models. We hypothesize that the performance gap stems from limited high-quality reasoning process data in current training sets. By constructing a specialized dataset focused on explicit problem-solving workflows (“worked solutions”), we demonstrate substantial improvements in planning capabilities from existing models. Additionally, we propose the Reasoning Enhancement Loop (REL), a method for generating synthetic worked solutions. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary New discoveries have shown that special language models can solve complex problems in a way that’s similar to how humans think. These models, like OpenAI’s O1, take a step-by-step approach to solving problems, which is different from other top-performing models. We think this difference is because current training data doesn’t include enough information about how people think and reason. To improve performance, we created a new dataset that focuses on how people solve problems (“worked solutions”). This helps existing models do better planning. Our idea is to use this approach to make language models even more powerful. |
