Large Pre Trained

Large pre-trained deep neural networks are revolutionizing various fields by providing powerful, adaptable models for diverse tasks. Current research focuses on efficiently adapting these large models to specific downstream applications, exploring techniques like lightweight adapters, parameter sharing, and fine-tuning strategies to minimize computational costs and improve performance. This work is significant because it addresses the challenges of deploying these massive models on resource-constrained devices and improves their effectiveness in specialized domains, impacting fields from robotics and computer vision to natural language processing and web information retrieval.