most citedLarge Language Models (LLMs) for Requirements Engineering (RE): A Systematic Literature Review

7 citations · 9 across the 4 of their papers we have counts for

collaborators

7 papers

cs.SE2026

RITA: A Tool for Automated Requirements Classification and Specification from Online User Feedback

Manjeshwar Aniruddh Mallya, Alessio Ferrari, Mohammad Amin Zadenoori +1

Context and motivation. Online user feedback is a valuable resource for requirements engineering, but its volume and noise make analysis difficult. Existing tools support individua…

cs.SE2025

From Online User Feedback to Requirements: Evaluating Large Language Models for Classification and Specification Tasks

Manjeshwar Aniruddh Mallya, Alessio Ferrari, Mohammad Amin Zadenoori +1

[Context and Motivation] Online user feedback provides valuable information to support requirements engineering (RE). However, analyzing online user feedback is challenging due to…

cs.SE2025

Does Model Size Matter? A Comparison of Small and Large Language Models for Requirements Classification

Mohammad Amin Zadenoori, Vincenzo De Martino, Jacek Dabrowski +2

[Context and motivation] Large language models (LLMs) show notable results in natural language processing (NLP) tasks for requirements engineering (RE). However, their use is compr…

cs.SE2025

Green Prompt Engineering: Investigating the Energy Impact of Prompt Design in Software Engineering

Vincenzo De Martino, Mohammad Amin Zadenoori, Xavier Franch +1

Language Models are increasingly applied in software engineering, yet their inference raises growing environmental concerns. Prior work has examined hardware choices and prompt len…

cs.SE20257 cited

Large Language Models (LLMs) for Requirements Engineering (RE): A Systematic Literature Review

Mohammad Amin Zadenoori, Jacek Dąbrowski, Waad Alhoshan +2

Large Language Models (LLMs) are finding applications in numerous domains, and Requirements Engineering (RE) is increasingly benefiting from their capabilities to assist with compl…

cs.CL20252 cited

How Effective are Generative Large Language Models in Performing Requirements Classification?

Waad Alhoshan, Alessio Ferrari, Liping Zhao

In recent years, transformer-based large language models (LLMs) have revolutionised natural language processing (NLP), with generative models opening new possibilities for tasks th…