Regularization

Attention Dropout

Attention Dropout is a type of dropout used in attention-based architectures, where elements are randomly dropped out of the softmax in the attention equation. For example, for scaled-dot product attention, we would drop elements from the first term:

$$ {\text{Attention}}(Q, K, V) = \text{softmax}\left(\frac{QK^{T}}{\sqrt{d_k}}\right)V $$

Papers


Paper Code Results Date Stars

Tasks


Task Papers Share
RAG 186 16.53%
Retrieval 143 12.71%
Question Answering 59 5.24%
Language Modelling 48 4.27%
Language Modeling 45 4.00%
Large Language Model 42 3.73%
Sentiment Analysis 21 1.87%
Text Classification 20 1.78%
Text Generation 19 1.69%

Components


Component Type
Dropout
Regularization

Categories