AILobstersabout 1 hour ago
Byte Transformers Outperform Subword Models
16 min read
Researchers find byte Transformers consistently outperform subword models as size scales, using token-superposition training and hash embeddings. The study shows 40% relative improvements on CUTE scores and 20% on OCRBench. Exploiting local structures via speculative decoding yields 3.4 times more accepted tokens than subword Transformers.
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