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 9556
2023 6060
2018 5105
2020 1369
2019 755
2018 683
2019 560
2019 548
2019 471
2020 169
2019 156
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2019 128
2020 120
2022 113
2020 108
2020 83
2020 78
2020 72
2020 66
2019 61
2020 59
2019 55
2020 50
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2019 45
2019 36
2019 30
2020 29
2000 29
2019 21
2021 19
2018 17
2021 16
2020 15
2020 14
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2019 12
2021 10
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2021 9
2022 8
2021 6
2020 6
2020 5
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2020 5
2021 3
2019 3
2021 3
2019 3
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2020 3
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2020 2
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2021 2
2021 2
2020 2
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2020 2
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2022 2
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2020 1
2020 1
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2019 1
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2018 1
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