A framework of variable-length sequence data preprocessing based on semantic perception
Deep learning frameworks generally adopt padding or truncation operations toward variable-length sequences in order to use efficient yet intensive batch training. However, padding leads to intensive memory consumption, and truncation inevitably loses the original semantic information. To address thi...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
EDP Sciences
2025-04-01
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| Series: | Xibei Gongye Daxue Xuebao |
| Subjects: | |
| Online Access: | https://www.jnwpu.org/articles/jnwpu/full_html/2025/02/jnwpu2025432p388/jnwpu2025432p388.html |
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