Transformer Based Pre Trained Language

Transformer-based pre-trained language models (PLMs) are revolutionizing natural language processing by learning powerful representations from massive text corpora. Current research focuses on improving efficiency (e.g., through quantization and pruning), addressing biases, and enhancing capabilities for diverse tasks (e.g., hate speech detection, reasoning, and multi-task learning) using architectures like BERT, T5, and GPT variants. These advancements are significantly impacting both the scientific understanding of language and the development of practical applications across various domains, including improved machine translation, question answering systems, and more responsible AI deployments.