Machine Learning, NLP, Computer Vision, Information Retrieval, Transformers.
pre-trained model L that we want to fine-tune on a new task D with a limited set of K training examples per class. For this, they study prompt-based fine-tuning, which instead of updating the model parameters with a supervised signal from task D, you concatenate the training sample with a prompt