Looping Beyond Twice: A Scalable Recipe for Looped Mixture-of-Experts
Looped Transformers introduce recurrent depth as a new scaling axis for LLMs: by repeatedly applying shared Transformer blocks, they increase effective depth without increasing parameter count. However, the benefits of looping remain unclear for large MoE LLMs under FLOPs-matched comparisons. The main reason is that th...
Di He, Peng-Xiang Li, Da Chang et al.
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