Papers by Md. Shahad Mahmud Chowdhury

2 papers
BanLemma: A Word Formation Dependent Rule and Dictionary Based Bangla Lemmatizer (2023.findings-emnlp)

Copied to clipboard

Challenge: Lemmatization holds significance in both natural language processing (NLP) and linguistics due to the highly inflected nature and morphological richness of Bangla text.
Approach: They propose linguistic rules for lemmatization and utilize a dictionary along with the rules to design a lemma specifically for Bangla.
Outcome: The proposed system achieves 96.36% accuracy when tested against a manually annotated test dataset.
BanNERD: A Benchmark Dataset and Context-Driven Approach for Bangla Named Entity Recognition (2025.findings-naacl)

Copied to clipboard

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.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations