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 9539
2023 6029
2018 5097
2020 1368
2019 754
2018 682
2019 559
2019 548
2019 466
2020 168
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2019 128
2020 120
2022 113
2020 108
2020 83
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2020 50
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2019 35
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2020 29
2000 29
2019 21
2021 18
2018 17
2021 16
2020 15
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2019 12
2021 10
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2022 8
2021 6
2020 6
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2020 5
2021 3
2019 3
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2020 2
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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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