DSML Reading Club #1 recording: Byte Latent Transformer

Yelaman Abdullin presented Byte Latent Transformer.

Modern LLMs rely on tokenization, which limits flexibility, reduces efficiency, and makes them vulnerable to rare and irregular inputs. The paper proposes Byte Latent Transformer (BLT), a new architecture that works directly with bytes. BLT uses dynamic patches that adapt to data complexity and, for the first time, matches the quality of tokenized models while providing better efficiency and scalability.

Watch the video: youtu.be/JN-adAvbAcs