Semantic Token

Semantic tokens represent meaningful units of information extracted from various data modalities, such as images, audio, and text, aiming to improve the efficiency and quality of downstream tasks in AI. Current research focuses on developing novel tokenization methods, often integrated into transformer architectures, to capture richer semantic content and improve model performance in areas like image generation, speech synthesis, and recommendation systems. This work is significant because effective semantic tokenization enhances model interpretability, reduces computational costs, and improves the accuracy and robustness of AI systems across diverse applications.