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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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Principais autores: Arshad Iqbal, Muhammad Inam Ul Haq, Abdul Wahid, Shad Muhammad, Muhammad Yahya, Abdul Shahid
פורמט: Artigo
שפה:Inglês
יצא לאור: IEEE 2026-01-01
סדרה:IEEE Access
נושאים:
Citation importance
explainable AI
SciBERT
sparse rationale extraction
HardKuma
interpretability
גישה מקוונת:https://ieeexplore.ieee.org/document/11499403/
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