A majority-vote ensemble of five independently fine-tuned GujaratiBERT models achieved the best entity-level F1 (0.8442) on Gujarati Naamapadam NER, ahead of the single-model baseline (0.8347) and all heterogeneous alternatives.
Recent Developments in Named Entity Recognition Techniques for Indian Languages: A Com- 17 prehensive Review,
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HomoEnsNER: Does Language Alignment Outperform Architectural Complexity in Gujarati Named Entity Recognition?
A majority-vote ensemble of five independently fine-tuned GujaratiBERT models achieved the best entity-level F1 (0.8442) on Gujarati Naamapadam NER, ahead of the single-model baseline (0.8347) and all heterogeneous alternatives.