Self Instruct

Self-Instruct is a technique for improving large language models (LLMs) by training them on instructions generated by the models themselves, minimizing the need for extensive human annotation. Current research focuses on refining the self-instruction generation process, including using reinforcement learning to optimize instruction quality and diversity, and employing ensembles of models to improve the reliability of generated data. This approach offers a more efficient and scalable method for creating high-quality instruction datasets, leading to significant improvements in LLM performance across various tasks and languages, and potentially reducing the reliance on proprietary, large language models.