Exploring the Design of Generative AI in Supporting Music-based Reminiscence for Older Adults

Exploring the Effectiveness of LLMs in Automated Logging Statement Generation: An Empirical Study

Fail, fail again, fail better: How players who enjoy challenging games persist after failure in {textquotedblleft}Celeste{textquotedblright}

Feature Encapsulation by Stages Using Grammatical Evolution

Effective Supports for Women Computer Science Academics: Practice Based Insights in an Irish Context

Empowering Patients Through Conversational Agents Enhancing Participation and Personalization in Healthcare

Energy loss calculation and voltage profile improvement for the rehabilitation of 0.4~kV low voltage distribution network (LVDN)

Enhancing Algorithmic Fairness: Integrative Approaches and Multi-Objective Optimization Application in Recidivism Models

Enhancing Program Synthesis with Large Language Models Using Many-Objective Grammar-Guided Genetic Programming

The ability to automatically generate code, i.e., program synthesis, is one of the most important applications of artificial intelligence (AI). Currently, two AI techniques are leading the way: large language models (LLMs) and genetic programming (GP) methods{textemdash}each with its strengths and weaknesses. While LLMs have shown success in program synthesis from a task description, they...

The Environmental Cost of Engineering Machine Learning-Enabled Systems: A Mapping Study

The integration of Machine Learning (ML) across public and industrial sectors has become widespread, posing unique challenges in comparison to conventional software development methods throughout the lifecycle of ML-Enabled Systems. Particularly, with the rising importance of ML platforms in software operations and the computational power associated with their frequent training, testing, and retraining, there is...