Synthesizer: Rethinking Self-Attention in Transformer Models

时间 2021-01-12

标签 NLP 机器学习深度学习繁體版

原文原文链接

Synthesizer: Rethinking Self-Attention in Transformer Models 这篇论文通过替换 Q × K T Q \times K^{T} Q×KTattention矩阵，发现Self-Attention中query-key-value dot product attention并不是不可或缺的。作者分别提出了Dense SynSynthesizer

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1. Google新作synthesizer：Rethinking Self-Attention in Transformer Models
2. selfattention
3. Google新作Synthesizer：我们还不够了解自注意力
4. Rethinking Performance Estimation in Neural Arc
5. selfattention记录
6. Transformer-XL: Unleashing the Potential of Attention Models
7. <Probabilistic Graphical Models>2 Graphical Models in Action
8. 如何理解SelfAttention
9. Rethinking RGB-D Salient Object Detection: Models, Datasets, and Large-Scale Benchmarks
10. transformer详解：transformer/ universal transformer/ transformer-XL

>>更多相关文章<<