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Matching papers

Multi-Head Attention Residuals

8 upvotes · 22 JUL 2026 · Cheng Luo, Zefan Cai, Junjie Hu

This paper improves the Transformer model by introducing Multi-Head Attention Residuals, which allows each sublayer to attend to different parts of the model's history, reducing the impact of disagreements between different feature subspaces. Practitioners might care because this could lead to better performance in large models.

transformersattention mechanismsresidual connectionsmulti-head attentionlarge language models