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 9608
2023 6122
2018 5116
2020 1379
2019 757
2018 691
2019 561
2019 554
2019 477
2020 175
2019 156
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2020 120
2022 113
2020 108
2020 83
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2020 50
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2020 29
2000 29
2019 22
2021 19
2018 18
2021 16
2020 15
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2020 13
2019 12
2021 10
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2022 8
2020 6
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2020 5
2021 3
2019 3
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2020 2
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2020 1
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2019 1
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2018 1
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