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cs.LG2026
A Few More Tokens Ahead: Reinforcing Parallelism in Diffusion LLMs
Jiahao Kuang, Yangfan Gao, Tao Gui +4
Parallel generation is widely regarded as an inherent advantage of diffusion large language models. Yet our fixed-quota evaluation of four representative models reveals severe degr…
cs.CL2026
Byte Language Models: Scaling, Emergent Abstractions, and Information Allocation
Jie Wang, Shiwei Luo, Qi Zhang +1
Tokenizer-free language models remove the inductive bias of fixed tokenizers by modeling text directly as bytes, but the resulting longer sequences substantially increase computati…