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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.LG2026
MLAfication: Efficiently Enabling High-Fidelity MLA for Modern LLMs
Zile Wang, Zhide Xie, Tao Ji
Multi-Head Latent Attention (MLA) compresses the KV cache into a latent representation, reducing inference memory and bandwidth. Existing MHA2MLA/TransMLA methods do not support QK…