BLT-D, BLT-S, and BLT-DV use block-wise diffusion training and speculative verification to enable parallel byte generation in byte-level LMs, cutting memory-bandwidth cost by over 50%.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
MobileLLM-Flash creates 350M-1.4B parameter LLMs via latency-guided search and attention skipping, delivering up to 1.8x faster prefill and 1.6x faster decode on mobile CPUs with comparable or better quality.
citing papers explorer
-
Fast Byte Latent Transformer
BLT-D, BLT-S, and BLT-DV use block-wise diffusion training and speculative verification to enable parallel byte generation in byte-level LMs, cutting memory-bandwidth cost by over 50%.
-
MobileLLM-Flash: Latency-Guided On-Device LLM Design for Industry Scale Deployment
MobileLLM-Flash creates 350M-1.4B parameter LLMs via latency-guided search and attention skipping, delivering up to 1.8x faster prefill and 1.6x faster decode on mobile CPUs with comparable or better quality.