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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
Format: Artigo
Sprog:Inglês
Udgivet: IEEE 2026-01-01
Serier:IEEE Access
Fag:
Citation importance
explainable AI
SciBERT
sparse rationale extraction
HardKuma
interpretability
Online adgang:https://ieeexplore.ieee.org/document/11499403/
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