Julie Kallini

PhD student at Stanford University researching tokenization, byte-level models, and the intersection of language models and linguistics.

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Mar 24, 2025 • 51min

Dynamic Token Merging for Efficient Byte-level Language Models with Julie Kallini - #724

Join Julie Kallini, a PhD student at Stanford, as she dives into the future of language models. Discover her groundbreaking work on MrT5, a model that tackles tokenization failures and enhances efficiency for multilingual tasks. Julie discusses the creation of 'impossible languages' and the insights they offer into language acquisition and model biases. Hear about innovative architecture improvements and the importance of adapting tokenization methods for underrepresented languages. A fascinating exploration at the intersection of linguistics and AI!