60 citations · 60 across the 4 of their papers we have counts for
4 papers
CodeT5-RNN: Reinforcing Contextual Embeddings for Enhanced Code Comprehension
Md Mostafizer Rahman, Ariful Islam Shiplu, Yutaka Watanobe +3
Contextual embeddings generated by LLMs exhibit strong positional inductive biases, which can limit their ability to fully capture long-range, order-sensitive dependencies in highl…
Large Language Models for Education and Research: An Empirical and User Survey-based Analysis
Md Mostafizer Rahman, Ariful Islam Shiplu, Md Faizul Ibne Amin +2
Pretrained Large Language Models (LLMs) have achieved remarkable success across diverse domains, with education and research emerging as particularly impactful areas. Among current…
Code Refactoring with LLM: A Comprehensive Evaluation With Few-Shot Settings
Md. Raihan Tapader, Md. Mostafizer Rahman, Ariful Islam Shiplu +2
In today's world, the focus of programmers has shifted from writing complex, error-prone code to prioritizing simple, clear, efficient, and sustainable code that makes programs eas…
RoBERTa-BiLSTM: A Context-Aware Hybrid Model for Sentiment Analysis
Md. Mostafizer Rahman, Ariful Islam Shiplu, Yutaka Watanobe +1
Effectively analyzing the comments to uncover latent intentions holds immense value in making strategic decisions across various domains. However, several challenges hinder the pro…