Cross-Tokenizer LLM Distillation through a Byte-Level Interface
Cross-tokenizer distillation (CTD), the transfer of knowledge from a teacher to a student language model when the two use different tokenizers, remains a largely unsolved problem. Existing approaches rely on heuristic strategies to align mismatched vocabularies, introducing considerable complexity. In this paper, we propose a simple but effective baseline called Byte-Level Distillation (BLD) which enables CTD by operating at a common interface across tokenizers: the byte level. In more detail, we convert the teacher's output distribution to byte-level probabilities, attach a lightweight byte-level decoder head to the student, and distill through this shared byte-level interface. Despite i...
| Authors | Avyav Kumar Singh, Yen-Chen Wu, Alexandru Cioba et al. |
|---|---|
| Primary category | cs.CL |
| Published | 8 April 2026 |
| Last updated at source | 13 April 2026 |
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