3 citations · 4 across the 5 of their papers we have counts for
5 papers
Exploring Bengali Religious Dialect Biases in Large Language Models with Evaluation Perspectives
Azmine Toushik Wasi, Raima Islam, Mst Rafia Islam +2
While Large Language Models (LLM) have created a massive technological impact in the past decade, allowing for human-enabled applications, they can produce output that contains ste…
SentiCSE: A Sentiment-aware Contrastive Sentence Embedding Framework with Sentiment-guided Textual Similarity
Jaemin Kim, Yohan Na, Kangmin Kim +2
Recently, sentiment-aware pre-trained language models (PLMs) demonstrate impressive results in downstream sentiment analysis tasks. However, they neglect to evaluate the quality of…
When SMILES have Language: Drug Classification using Text Classification Methods on Drug SMILES Strings
Azmine Toushik Wasi, Šerbetar Karlo, Raima Islam +2
Complex chemical structures, like drugs, are usually defined by SMILES strings as a sequence of molecules and bonds. These SMILES strings are used in different complex machine lear…
Fairness and Privacy-Preserving in Federated Learning: A Survey
Taki Hasan Rafi, Faiza Anan Noor, Tahmid Hussain +1
Federated learning (FL) as distributed machine learning has gained popularity as privacy-aware Machine Learning (ML) systems have emerged as a technique that prevents privacy leaka…
A Generalized Look at Federated Learning: Survey and Perspectives
Taki Hasan Rafi, Faiza Anan Noor, Tahmid Hussain +2
Federated learning (FL) refers to a distributed machine learning framework involving learning from several decentralized edge clients without sharing local dataset. This distribute…