Latent Token

Latent tokens represent a compressed, semantically meaningful representation of data, often used to improve efficiency and interpretability in various machine learning models. Current research focuses on developing efficient architectures, such as diffusion transformers and recurrent interface networks, that leverage latent tokens to reduce computational complexity in tasks like image and video generation, while also exploring their use in enhancing model interpretability and controlling model behavior. This approach has significant implications for improving the scalability and performance of large language and vision models, as well as for advancing our understanding of how these models process information.