Language Models are Few-Shot Learners

This paper introduces the concept of using large language models to perform various tasks with only a few examples, demonstrating that these models can achieve strong results without task-specific training. It explores the capabilities of GPT-3, a massive language model, in few-shot learning scenarios across different NLP tasks, showcasing its potential for generalization and adaptation.