Synthesizer: Rethinking Self-Attention in Transformer Models
Synthesizer: Rethinking Self-Attention in Transformer Models 這篇論文通過替換 Q × K T Q \times K^{T} Q×KTattention矩陣，發現Self-Attention中query-key-value dot product attention並不是不可或缺的。作者分別提出了Dense SynSynthesizer
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相關文章
- 1. Google新作synthesizer：Rethinking Self-Attention in Transformer Models
- 2. selfattention
- 3. Google新作Synthesizer：我們還不夠了解自注意力
- 4. Rethinking Performance Estimation in Neural Arc
- 5. selfattention記錄
- 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詳解：transformer/ universal transformer/ transformer-XL