Kronecker Embeddings replace learned embedding tables with a deterministic byte-level character-position factorization and single projection, reducing parameters over 90% with reported gains in loss and robustness on language modeling tasks.
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Kronecker Embeddings: Byte-Level Structured Token Representations for Parameter-Efficient Language Models
Kronecker Embeddings replace learned embedding tables with a deterministic byte-level character-position factorization and single projection, reducing parameters over 90% with reported gains in loss and robustness on language modeling tasks.