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Byte Latent Transformer: Patches Scale Better Than Tokens

Pagnoni et al., 2025, Byte Latent Transformer (Proceedings of the 63rd Annual Meeting of ACL (Volume 1: Long Papers))

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3 BLT Architecture

  1. What are the three modules of BLT?
    A lightweight local encoder that turns bytes into patch representations; a large latent global Transformer over patches (block-causal, most of the FLOPs); and a lightweight local decoder that turns each output patch representation back into the next patch’s bytes.
    • Pagnoni et al., 2025, Byte Latent Transformer (Proceedings of the 63rd Annual Meeting of ACL (Volume 1: Long Papers)), §3, p. 9240

Source

  • Artidoro Pagnoni, Ramakanth Pasunuru, Pedro Rodriguez, John Nguyen, Benjamin Muller, Margaret Li, Chunting Zhou, Lili Yu, Jason E. Weston, Luke Zettlemoyer, Gargi Ghosh, Mike Lewis, Ari Holtzman and Srini Iyer. 2025. Byte Latent Transformer: Patches Scale Better Than Tokens. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 9238–9258. License: CC BY 4.0. Flashcards adapted from this work. doi:10.18653/v1/2025.acl-long.453 https://aclanthology.org/2025.acl-long.453/