Softmax-free Vision Transformer With Linear Complexity: Achieving a Superior Accuracy/Complexity Trade-off | Synced

Researchers from Fudan University, University of Surrey and Huawei Noah’s Ark Lab identify the limitations of quadratic complexity for vision transformers (ViTs) as rooted in keeping the softmax self-attention during approximations. The team proposes the first softmax-free transformer (SOFT), which reduces the self-attention computation to linear complexity, achieving a superior trade-off between accuracy and complexity.