ToMoE: Converting Dense LLMs to Mixture-of-Experts
August 24, 2026
The ToMoE method uses differentiable dynamic structural pruning to convert dense LLMs into Mixture-of-Experts (MoE) architectures. This approach reduces active parameter counts during inference without the performance loss associated with permanent parameter deletion.
HOW THIS AFFECTS YOU
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builderYou may be able to deploy more efficient, lower-latency versions of dense models using this conversion technique.
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researcherThis presents a new way to optimize model efficiency through dynamic structural changes.