Shelf Model

"Shelf models" refer to the utilization of pre-trained models, developed for one task, and applied directly ("off-the-shelf") to a different task without further training or with minimal fine-tuning. Current research focuses on exploring the effectiveness of various pre-trained architectures, including Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs), across diverse applications like image recognition, natural language processing, and robotics. This approach offers significant advantages in terms of efficiency and resource reduction, particularly valuable for resource-constrained environments and tasks with limited labeled data, while also highlighting and mitigating biases present in the original training data.