5 papers
Pseudo2CodeQA: A Benchmark for LLM-Based Structured Algorithmic Reasoning in Code Generation
Shadikur Rahman, Umme Ayman Koana, Syed Muhammad Danish
Large Language Models (LLMs) have achieved impressive performance in natural language-to-code generation; however, their ability to follow structured algorithmic reasoning remains…
RefactorCoderQA: Benchmarking LLMs for Multi-Domain Coding Question Solutions in Cloud and Edge Deployment
Shadikur Rahman, Aroosa Hameed, Gautam Srivastava +1
To optimize the reasoning and problem-solving capabilities of Large Language Models (LLMs), we propose a novel cloud-edge collaborative architecture that enables a structured multi…
Automated Research Article Classification and Recommendation Using NLP and ML
Shadikur Rahman, Hasibul Karim Shanto, Umme Ayman Koana +1
In the digital era, the exponential growth of scientific publications has made it increasingly difficult for researchers to efficiently identify and access relevant work. This pape…
Toward Green Code: Prompting Small Language Models for Energy-Efficient Code Generation
Humza Ashraf, Syed Muhammad Danish, Shadikur Rahman +1
There is a growing concern about the environmental impact of large language models (LLMs) in software development, particularly due to their high energy use and carbon footprint. S…
Energy-Aware Code Generation with LLMs: Benchmarking Small vs. Large Language Models for Sustainable AI Programming
Humza Ashraf, Syed Muhammad Danish, Aris Leivadeas +2
Large Language Models (LLMs) are widely used for code generation. However, commercial models like ChatGPT require significant computing power, which leads to high energy use and ca…