Sequence Generation Task

Sequence generation is a core task in natural language processing (NLP) aiming to create new text sequences based on input data or instructions. Current research focuses on improving efficiency and performance through techniques like knowledge distillation, reinforcement learning for reward optimization, and innovative model architectures such as transformers with adaptive masking or efficient linear variants. These advancements are driving progress in diverse applications, including machine translation, question answering, text summarization, and even specialized domains like music composition and lane detection in autonomous driving. The resulting improvements in accuracy, speed, and resource efficiency are significantly impacting both NLP research and real-world applications.