Learning to summarize with human feedback

OpenAI Blog · 5 years ago

Researchers trained language models to summarize text more effectively by using reinforcement learning guided by human feedback rather than traditional supervised learning methods. The approach involved collecting human preferences on model-generated summaries and using those preferences to refine the training process. This method produced models that better aligned with human judgments about summary quality compared to models trained with standard techniques.