AI RESEARCH
Kronecker Embeddings: Byte-Level Structured Token Representations for Parameter-Efficient Language Models
arXiv CS.LG
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ArXi:2605.29459v1 Announce Type: cross Large language models route every input through a learned embedding table of shape |V| x d_model, consuming hundreds of millions to billions of trainable parameters at frontier scale. We