SciBERT-Based Interpretable Framework for Citation Influence Classification Using Sparse Rationale Extraction
Assessing the influence of scientific citations is critical to understanding the impact of scholarly research beyond the raw citation counts. Recent neural models achieve strong performance in citation classification but typically function as black boxes, limiting their suitability for transparent b...
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| Главные авторы: | , , , , , |
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| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
IEEE
2026-01-01
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| Серии: | IEEE Access |
| Предметы: | |
| Online-ссылка: | https://ieeexplore.ieee.org/document/11499403/ |
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