6 citations · 24 across the 10 of their papers we have counts for
11 papers
Echoes of Unrest: A Multimodal NLP Framework for Early Warning of Fake News and Violence-Driven Mob Activity
Md. Maruf Bangabashi, Tahmid Hasan, Golam Mahmud +3
Rapid growth in social media has transformed global communication by enabling fast information exchange, but it has also accelerated the spread of misinformation. Fake news, manipu…
Contrastive Learning for API Aspect Analysis
G. M. Shahariar, Tahmid Hasan, Anindya Iqbal +1
We present a novel approach - CLAA - for API aspect detection in API reviews that utilizes transformer models trained with a supervised contrastive loss objective function. We eval…
GEMv2: Multilingual NLG Benchmarking in a Single Line of Code
Sebastian Gehrmann, Abhik Bhattacharjee, Abinaya Mahendiran +74
Evaluation in machine learning is usually informed by past choices, for example which datasets or metrics to use. This standardization enables the comparison on equal footing using…
BanglaNLG and BanglaT5: Benchmarks and Resources for Evaluating Low-Resource Natural Language Generation in Bangla
Abhik Bhattacharjee, Tahmid Hasan, Wasi Uddin Ahmad +1
This work presents BanglaNLG, a comprehensive benchmark for evaluating natural language generation (NLG) models in Bangla, a widely spoken yet low-resource language. We aggregate s…
CrossSum: Beyond English-Centric Cross-Lingual Summarization for 1,500+ Language Pairs
Abhik Bhattacharjee, Tahmid Hasan, Wasi Uddin Ahmad +3
We present CrossSum, a large-scale cross-lingual summarization dataset comprising 1.68 million article-summary samples in 1,500+ language pairs. We create CrossSum by aligning para…
Environmental Impacts of Personal Protective Clothing Used to Combat COVID-19
Mohammad Abbas Uddin, Shaila Afroj, Tahmid Hasan +3
Personal protective clothing is critical to shield users from highly infectious diseases including COVID-19. Such clothing is predominantly single-use, made of plastic-based synthe…
XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages
Tahmid Hasan, Abhik Bhattacharjee, Md Saiful Islam +5
Contemporary works on abstractive text summarization have focused primarily on high-resource languages like English, mostly due to the limited availability of datasets for low/mid-…
CoDesc: A Large Code-Description Parallel Dataset
Masum Hasan, Tanveer Muttaqueen, Abdullah Al Ishtiaq +6
Translation between natural language and source code can help software development by enabling developers to comprehend, ideate, search, and write computer programs in natural lang…
BERT2Code: Can Pretrained Language Models be Leveraged for Code Search?
Abdullah Al Ishtiaq, Masum Hasan, Md. Mahim Anjum Haque +5
Millions of repetitive code snippets are submitted to code repositories every day. To search from these large codebases using simple natural language queries would allow programmer…
BanglaBERT: Language Model Pretraining and Benchmarks for Low-Resource Language Understanding Evaluation in Bangla
Abhik Bhattacharjee, Tahmid Hasan, Wasi Uddin Ahmad +5
In this work, we introduce BanglaBERT, a BERT-based Natural Language Understanding (NLU) model pretrained in Bangla, a widely spoken yet low-resource language in the NLP literature…
Not Low-Resource Anymore: Aligner Ensembling, Batch Filtering, and New Datasets for Bengali-English Machine Translation
Tahmid Hasan, Abhik Bhattacharjee, Kazi Samin +4
Despite being the seventh most widely spoken language in the world, Bengali has received much less attention in machine translation literature due to being low in resources. Most p…