AI RESEARCH
2Mamba2Furious: Linear in Complexity, Competitive in Accuracy
arXiv CS.LG
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ArXi:2602.17363v2 Announce Type: replace Linear attention transformers have become a strong alternative to softmax attention due to their efficiency. However, linear attention tends to be less expressive and results in reduced accuracy compared to softmax attention. To bridge the accuracy gap between softmax attention and linear attention, we manipulate Mamba-2, a very strong linear attention variant. We first simplify Mamba-2 down to its most fundamental and important components, evaluating which specific choices make it most accurate.