Large language models in computer science education: A systematic literature review

N Raihan, ML Siddiq, JCS Santos… - Proceedings of the 56th …, 2025 - dl.acm.org
Large language models (LLMs) are becoming increasingly better at a wide range of Natural
Language Processing tasks (NLP), such as text generation and understanding. Recently …

Mojobench: Language modeling and benchmarks for mojo

N Raihan, J Santos, M Zampieri - arxiv preprint arxiv:2410.17736, 2024 - arxiv.org
The recently introduced Mojo programming language (PL) by Modular, has received
significant attention in the scientific community due to its claimed significant speed boost …

mHumanEval--A Multilingual Benchmark to Evaluate Large Language Models for Code Generation

N Raihan, A Anastasopoulos, M Zampieri - arxiv preprint arxiv …, 2024 - arxiv.org
Recent advancements in large language models (LLMs) have significantly enhanced code
generation from natural language prompts. The HumanEval Benchmark, developed by …

Code LLMs: A Taxonomy-based Survey

N Raihan, C Newman… - 2024 IEEE International …, 2024 - ieeexplore.ieee.org
Large language models (LLMs) have demonstrated remarkable capabilities across various
NLP tasks and have recently expanded their impact to coding tasks, bridging the gap …

On the performance of large language models on introductory programming assignments

N Raihan, D Goswami, SSC Puspo, ML Siddiq… - 2024 - researchsquare.com
Recent advances in artificial intelligence (AI), machine learning (ML), and natural language
processing (NLP) have led to the development of a new generation of Large Language …