5 papers · 1 filter
Compute Optimal Tokenization
Tomasz Limisiewicz, Artidoro Pagnoni, Srini Iyer +6
Scaling laws enable the optimal selection of data amount and language model size, yet the impact of the data unit, the token, on this relationship remains underexplored. In this wo…
Fast Byte Latent Transformer
Julie Kallini, Artidoro Pagnoni, Tomasz Limisiewicz +5
Recent byte-level language models (LMs) match the performance of token-level models without relying on subword vocabularies, yet their utility is limited by slow, byte-by-byte auto…
Bolmo: Byteifying the Next Generation of Language Models
Benjamin Minixhofer, Tyler Murray, Tomasz Limisiewicz +6
Recent advances in generative AI have been largely driven by large language models (LLMs), deep neural networks that operate over discrete units called tokens. To represent text, t…
Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation
Tomasz Limisiewicz, David MareÄek, Tomáš Musil
Mitigation of biases, such as language models' reliance on gender stereotypes, is a crucial endeavor required for the creation of reliable and useful language technology. The cruci…
Teaching LLMs at Charles University: Assignments and Activities
JindÅich Helcl, ZdenÄk Kasner, OndÅej DuÅ¡ek +4
This paper presents teaching materials, particularly assignments and ideas for classroom activities, from a new course on large language models (LLMs) taught at Charles University.…