Papers by Faisal Ahamed Khan

2 papers
BanSuite: A Unified Toolkit and Software Platform for Low-Resource NLP in Bangla (2026.eacl-demo)

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Challenge: Existing efforts to improve Bangla's NLP performance have focused on isolated tasks such as Part-of-Speech tagging and Named Entity Recognition (NER) but comprehensive, integrated systems for core NLP tasks such Shallow Parsing and Dependency Parser are largely absent.
Approach: They propose to integrate a large-scale, manually annotated Bangla Treebank with high-quality pretrained models for POS tagging, NER, shallow parsing, and dependency parse.
Outcome: The proposed system achieves strong in-domain baseline performance while maintaining high efficiency in resource usage.
BanNERD: A Benchmark Dataset and Context-Driven Approach for Bangla Named Entity Recognition (2025.findings-naacl)

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Challenge: In a cross-dataset evaluation, models trained on BanNERD consistently outperformed those trained on four existing Bangla NER datasets.
Approach: They propose to use Bangla as a language to create the most extensive human-annotated and validated Bangla NLP dataset.
Outcome: The proposed method outperforms existing methods on Bangla NER datasets and performs competitively on English datasets.

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