3 papers
cs.SE2026
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…
cs.AI2025
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…
cs.SE2025
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…