BlockTrain partitions models into block-local diffusion objectives that train near end-to-end WikiText quality with one-block worker memory, real WAN transport, and one-sweep distributed serving.
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2 Pith papers cite this work. Polarity classification is still indexing.
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FoMoE partitions expert layers across workers in MoE LLMs, skips non-resident experts, and reports up to 1.42x lower communication than baselines plus 1.4x throughput gains while maintaining stable routing.
citing papers explorer
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Decentralised AI Training and Inference with BlockTrain
BlockTrain partitions models into block-local diffusion objectives that train near end-to-end WikiText quality with one-block worker memory, real WAN transport, and one-sweep distributed serving.
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FoMoE: Breaking the Full-Replica Barrier with a Federation of MoEs
FoMoE partitions expert layers across workers in MoE LLMs, skips non-resident experts, and reports up to 1.42x lower communication than baselines plus 1.4x throughput gains while maintaining stable routing.