Self-Instruct: Aligning Language Models with Self-Generated Instructions

Key Points

• The aim is to align language models with instructions generated by the models themselves for improved performance.
• Developed a framework for self-generating instructions for language models.
• Evaluated the effectiveness of the alignment through various comparison metrics.
• Utilized a dataset of NLP tasks to assess model performance after alignment.
• Significant improvements in task performance were observed after alignment with self-generated instructions.
• Achieved an increase of 15% in accuracy on standard NLP benchmarks with aligned models (p<0.001).
• The alignment process reduced response time by 20%, indicating increased efficiency.