Kronecker Embeddings: Byte-Level Structured Token Representations for Parameter-Efficient Language Models 事件

Kronecker Embeddings: Byte-Level Structured Token Representations for Parameter-Efficient Language Models arXiv:2605.29459v1 Announce Type: new Abstract: 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 introduce Kronecker Embeddings, a deterministic byte-level character-position factorization that replaces this table with a fixed encoder and a single learned