Representative papers are highlighted.

2026

ANCHOLIK-NER: A benchmark dataset for bangla regional named entity recognition
PLOS ONE
ANCHOLIK-NER: A benchmark dataset for bangla regional named entity recognition

Bidyarthi Paul; Faika Fairuj Preotee; Shuvashis Sarker; Shamim Rahim Refat; Shifat Islam; Tashreef Muhammad; Mohammad Ashraful Hoque; Shahriar Manzoor.

PLOS ONE 2026

TL;DR: We introduce ANCHOLIK-NER, the first benchmark dataset for Bangla regional named entity recognition, and show that BanglaBERT provides the strongest baseline across five major dialect regions.

#Bangla NLP#Named Entity Recognition#Regional Dialects#Dataset#BanglaBERT

[PLOS ONE]

ANCHOLIK-NER: A benchmark dataset for bangla regional named entity recognition

Bidyarthi Paul; Faika Fairuj Preotee; Shuvashis Sarker; Shamim Rahim Refat; Shifat Islam; Tashreef Muhammad; Mohammad Ashraful Hoque; Shahriar Manzoor.

PLOS ONE 2026

TL;DR: We introduce ANCHOLIK-NER, the first benchmark dataset for Bangla regional named entity recognition, and show that BanglaBERT provides the strongest baseline across five major dialect regions.

#Bangla NLP#Named Entity Recognition#Regional Dialects#Dataset#BanglaBERT

[PLOS ONE]

PLOS ONE

2025

BIDWESH: A Bangla regional based hate speech detection dataset
arXiv
BIDWESH: A Bangla regional based hate speech detection dataset

Azizul Hakim Fayaz; MD Uddin; Rayhan Uddin Bhuiyan; Zakia Sultana; Md Samiul Islam; Bidyarthi Paul; Tashreef Muhammad; Shahriar Manzoor.

arXiv 2025

TL;DR: We introduce BIDWESH, the first multi-dialectal Bangla hate speech dataset, covering Barishal, Noakhali, and Chittagong dialects to support dialect-aware hate speech detection and fairer content moderation.

#Bangla NLP#Hate Speech Detection#Regional Dialects#Dataset#Low-resource NLP

[Arxiv]

BIDWESH: A Bangla regional based hate speech detection dataset

Azizul Hakim Fayaz; MD Uddin; Rayhan Uddin Bhuiyan; Zakia Sultana; Md Samiul Islam; Bidyarthi Paul; Tashreef Muhammad; Shahriar Manzoor.

arXiv 2025

TL;DR: We introduce BIDWESH, the first multi-dialectal Bangla hate speech dataset, covering Barishal, Noakhali, and Chittagong dialects to support dialect-aware hate speech detection and fairer content moderation.

#Bangla NLP#Hate Speech Detection#Regional Dialects#Dataset#Low-resource NLP

[Arxiv]

arXiv
Leveraging large language models for bengali math word problem solving with chain of thought reasoning
TALLIP
Leveraging large language models for bengali math word problem solving with chain of thought reasoning

Bidyarthi Paul; Jalisha Jashim Era; Mirazur Rahman Zim; Tahmid Sattar Aothoi; Faisal Muhammad Shah.

ACM TALLIP 2025

TL;DR: We introduce SOMADHAN, a Bengali math word problem dataset with step-by-step solutions, and show that chain-of-thought prompting substantially improves LLM performance on complex Bengali mathematical reasoning tasks.

#Bangla NLP#Math Word Problems#Large Language Models#Chain-of-Thought#Reasoning

[ACM TALLIP] [Arxiv]

Leveraging large language models for bengali math word problem solving with chain of thought reasoning

Bidyarthi Paul; Jalisha Jashim Era; Mirazur Rahman Zim; Tahmid Sattar Aothoi; Faisal Muhammad Shah.

ACM TALLIP 2025

TL;DR: We introduce SOMADHAN, a Bengali math word problem dataset with step-by-step solutions, and show that chain-of-thought prompting substantially improves LLM performance on complex Bengali mathematical reasoning tasks.

#Bangla NLP#Math Word Problems#Large Language Models#Chain-of-Thought#Reasoning

[ACM TALLIP] [Arxiv]

TALLIP

2024

Empowering bengali education with ai: Solving bengali math word problems through transformer models
ICCIT
Empowering bengali education with ai: Solving bengali math word problems through transformer models

Jalisha Jashim Era; Bidyarthi Paul; Tahmid Sattar Aothoi; Mirazur Rahman Zim; Faisal Muhammad Shah.

ICCIT 2024

TL;DR: We solve Bengali math word problems using transformer-based models and introduce the PatiGonit dataset, showing that mT5 achieves the best performance for translating problems into equations.

#Bangla NLP#Math Word Problems#Transformer Models#Bengali Education#Low-resource NLP

[IEEE] [Arxiv]

Empowering bengali education with ai: Solving bengali math word problems through transformer models

Jalisha Jashim Era; Bidyarthi Paul; Tahmid Sattar Aothoi; Mirazur Rahman Zim; Faisal Muhammad Shah.

ICCIT 2024

TL;DR: We solve Bengali math word problems using transformer-based models and introduce the PatiGonit dataset, showing that mT5 achieves the best performance for translating problems into equations.

#Bangla NLP#Math Word Problems#Transformer Models#Bengali Education#Low-resource NLP

[IEEE] [Arxiv]

ICCIT
Bridging dialects: Translating standard bangla to regional variants using neural models
ICCIT
Bridging dialects: Translating standard bangla to regional variants using neural models

Md Arafat Alam Khandaker; Ziyan Shirin Raha; Bidyarthi Paul; Tashreef Muhammad.

ICCIT 2024

TL;DR: We translate standard Bangla into multiple regional dialects using neural machine translation models and show that BanglaT5 performs best for capturing dialect-specific linguistic variations.

#Bangla NLP#Dialect Translation#Neural Machine Translation#BanglaT5#Low-resource NLP

[IEEE] [Arxiv]

Bridging dialects: Translating standard bangla to regional variants using neural models

Md Arafat Alam Khandaker; Ziyan Shirin Raha; Bidyarthi Paul; Tashreef Muhammad.

ICCIT 2024

TL;DR: We translate standard Bangla into multiple regional dialects using neural machine translation models and show that BanglaT5 performs best for capturing dialect-specific linguistic variations.

#Bangla NLP#Dialect Translation#Neural Machine Translation#BanglaT5#Low-resource NLP

[IEEE] [Arxiv]

ICCIT
Analyzing emotions in Bangla social media comments using machine learning and LIME
MIET
Analyzing emotions in Bangla social media comments using machine learning and LIME

Bidyarthi Paul; SM Musfiqur Rahman; Dipta Biswas; Md Ziaul Hasan; Md Zahid Hossain.

MIET 2024

TL;DR: We analyze Bangla social media comments for emotion detection using machine learning and deep learning models, and use LIME to explain model predictions for better interpretability.

#Bangla NLP#Emotion Analysis#Machine Learning#LIME#Social Media Analysis

[Springer] [Arxiv]

Analyzing emotions in Bangla social media comments using machine learning and LIME

Bidyarthi Paul; SM Musfiqur Rahman; Dipta Biswas; Md Ziaul Hasan; Md Zahid Hossain.

MIET 2024

TL;DR: We analyze Bangla social media comments for emotion detection using machine learning and deep learning models, and use LIME to explain model predictions for better interpretability.

#Bangla NLP#Emotion Analysis#Machine Learning#LIME#Social Media Analysis

[Springer] [Arxiv]

MIET
Improving Bangla regional dialect detection using BERT, LLMs, and XAI
COMPAS
Improving Bangla regional dialect detection using BERT, LLMs, and XAI

Bidyarthi Paul; Faika Fairuj Preotee; Shuvashis Sarker; Tashreef Muhammad.

COMPAS 2024

TL;DR: We improve Bangla regional dialect detection by comparing BERT-based models and large language models, and use LIME to interpret model predictions across multiple dialect regions.

#Bangla NLP#Dialect Detection#BERT#LLM#XAI

[IEEE]

Improving Bangla regional dialect detection using BERT, LLMs, and XAI

Bidyarthi Paul; Faika Fairuj Preotee; Shuvashis Sarker; Tashreef Muhammad.

COMPAS 2024

TL;DR: We improve Bangla regional dialect detection by comparing BERT-based models and large language models, and use LIME to interpret model predictions across multiple dialect regions.

#Bangla NLP#Dialect Detection#BERT#LLM#XAI

[IEEE]

COMPAS