Methods › General › Regularization › Embedding Dropout

Embedding Dropout

64 papers tagged archive 2025-07-28

Introduced by Yarin Gal et al. in A Theoretically Grounded Application of Dropout in Recurrent Neural Networks

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

Embedding Dropout is equivalent to performing dropout on the embedding matrix at a word level, where the dropout is broadcast across all the word vector’s embedding. The remaining non-dropped-out word embeddings are scaled by 1/(1-pₑ) where pₑ is the probability of embedding dropout. As the dropout occurs on the embedding matrix that is used for a full forward and backward pass, this means that all occurrences of a specific word will disappear within that pass, equivalent to performing variational dropout on the connection between the one-hot embedding and the embedding lookup.

Source: Merity et al, Regularizing and Optimizing LSTM Language Models

PaperSourceSee Code · salesforce/awd-lstm-lm

Papers archive 2025-07-28

30 shown of 64, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

20 shown of 85 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Language Modelling23
Language Modeling20
Text Classification16
Transfer Learning16
General Classification15
text-classification11
Sentiment Analysis10
Classification8
Translation5
Word Embeddings5
Language Identification4
Machine Translation4
Decision Making3
Deep Learning3
Hate Speech Detection3
Sentence3
Sentiment Classification3
Articles2
BIG-bench Machine Learning2
Image Classification2

Usage over time archive 2025-07-28

Papers per year tagged with Embedding Dropout: 2015 to 2025, peak 17 17 0 2015: 1 paper 2015 2016: 0 papers 2016 2017: 2 papers 2017 2018: 4 papers 2018 2019: 17 papers 2019 2020: 16 papers 2020 2021: 14 papers 2021 2022: 1 paper 2022 2023: 4 papers 2023 2024: 4 papers 2024 2025: 1 paper 2025
Papers per year the archive tags with this method, by the paper's archive date (64 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Regularization

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections