BERT Fine-Tuning for Software Requirement Classification: Impact of Model Components and Dataset Size
Recent advances in natural language processing (NLP) have enabled the automation of Software Requirements Classification (SRC), particularly through fine-tuning models such as Bidirectional Encoder Representations from Transformers (BERTs). While BERT-based models have shown promising results, the i...
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| Auteurs principaux: | , , |
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| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
MDPI AG
2025-11-01
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| Collection: | Information |
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| Accès en ligne: | https://www.mdpi.com/2078-2489/16/11/981 |
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