Next Token Prediction

Next-token prediction (NTP) is a machine learning technique where models predict the probability distribution of the next token in a sequence, primarily used to train large language models (LLMs). Current research focuses on improving NTP's efficiency and effectiveness through architectural innovations like encoder-only transformers and algorithmic enhancements such as multi-token prediction and selective language modeling, aiming to mitigate issues like memorization and hallucinations. The widespread use of NTP in training LLMs makes understanding its limitations and optimizing its performance crucial for advancing both the theoretical understanding of LLMs and their practical applications in various fields.