LNLF-BERT: Transformer for Long Document Classification With Multiple Attention Levels
Transformer-based models, such as Bidirectional Encoder Representations from Transformers (BERT), cannot process long sequences because their self-attention operation scales quadratically with the sequence length. To remedy this, we introduce the Look Near and Look Far BERT (LNLF-BERT) with a two-le...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10744540/ |
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