activity
20202024
most citedBanglaBERT: Language Model Pretraining and Benchmarks for Low-Resource Language Understanding Evaluation in Bangla

6 citations · 26 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CL2024★ 1 cited

Multi-ToM: Evaluating Multilingual Theory of Mind Capabilities in Large Language Models

Jayanta Sadhu, Ayan Antik Khan, Noshin Nawal +3

Theory of Mind (ToM) refers to the cognitive ability to infer and attribute mental states to oneself and others. As large language models (LLMs) are increasingly evaluated for soci…

cs.CL2024

An Empirical Study on the Characteristics of Bias upon Context Length Variation for Bangla

Jayanta Sadhu, Ayan Antik Khan, Abhik Bhattacharjee +1

Pretrained language models inherently exhibit various social biases, prompting a crucial examination of their social impact across various linguistic contexts due to their widespre…

cs.CV2024★ 6 cited

IllusionVQA: A Challenging Optical Illusion Dataset for Vision Language Models

Haz Sameen Shahgir, Khondker Salman Sayeed, Abhik Bhattacharjee +3

The advent of Vision Language Models (VLM) has allowed researchers to investigate the visual understanding of a neural network using natural language. Beyond object classification…

cs.CL2022★ 1 cited

BanglaParaphrase: A High-Quality Bangla Paraphrase Dataset

Ajwad Akil, Najrin Sultana, Abhik Bhattacharjee +1

In this work, we present BanglaParaphrase, a high-quality synthetic Bangla Paraphrase dataset curated by a novel filtering pipeline. We aim to take a step towards alleviating the l…

cs.CL2022★ 3 cited

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…

cs.CL2022★ 2 cited

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…

cs.CL2021★ 6 cited

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…

cs.CL2021

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-…

cs.CL2021★ 6 cited

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…

cs.CL2020★ 1 cited

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…