Reinforcement learning on incorrect responses helps models identify and unlearn 'spurious correlations'—incorrect intermediate steps that lead to correct final answers—scaling synthetic dataset efficiency by eight-fold compared to standard positive-only fine-tuning.

Authors

• Person: Not available Organization: arXiv
  A Survey on the Theory and Mechanism of Large Language Models

Sources

• A Survey on the Theory and Mechanism of Large Language Models arxiv.org arXiv via serper

Referenced by nodes (3)

• reinforcement learning concept
• fine-tuning concept
• Synthetic data concept