Papers with fine-tuning golden-standard Chain-of-Thought
Can LLMs Learn from Previous Mistakes? Investigating LLMs’ Errors to Boost for Reasoning (2024.acl-long)
Copied to clipboard
| Challenge: | Recent studies have shown the benefits to LLMs from fine-tuning golden-standard Chain-of-Thought rationales or using them as correct examples in few-shot prompting. |
| Approach: | They propose a new benchmark to test the effectiveness of large language models by leveraging errors to enhance reasoning capabilities. |
| Outcome: | The proposed methods can be used to fine-tune models in correct and incorrect domains, rather than tuning models to learn ground truth in traditional methods. |