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DARTree achieves a staggering 9.73脳 speedup in autoregressive decoding while accepting nearly 99% more tokens per round than existing methods.
Attention sinks, considered essential in autoregressive language models, turn out to be surprisingly prunable in diffusion language models, leading to better efficiency.
