Transformers

Transformers are a type of neural network architecture that have several properties that make them effective for modeling data with long-range dependencies. They generally feature a combination of multi-headed attention mechanisms, residual connections, layer normalization, feedforward connections, and positional embeddings.

Subcategories

Method Year Papers
2017 9443
2023 5880
2018 5073
2020 1350
2019 749
2018 671
2019 554
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2022 112
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2000 28
2019 21
2021 18
2018 17
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2019 11
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