1 code implementation • 27 Mar 2024 • Harsh Patel, Dominique Boucher, Emad Fallahzadeh, Ahmed E. Hassan, Bram Adams
This paper investigates the complexities of integrating Large Language Models (LLMs) into software products, with a focus on the challenges encountered for determining their readiness for release.
1 code implementation • 25 Mar 2024 • Marcos Macedo, Yuan Tian, Filipe R. Cogo, Bram Adams
Code translation between programming languages is a long-existing and critical task in software engineering, facilitating the modernization of legacy systems, ensuring cross-platform compatibility, and enhancing software performance.
1 code implementation • 25 Feb 2024 • Zhimin Zhao, Yihao Chen, Abdul Ali Bangash, Bram Adams, Ahmed E. Hassan
In machine learning (ML), efficient asset management, including ML models, datasets, algorithms, and tools, is vital for resource optimization, consistent performance, and a streamlined development lifecycle.
no code implementations • 22 Dec 2023 • Ernesto Lang Oreamuno, Rohan Faiyaz Khan, Abdul Ali Bangash, Catherine Stinson, Bram Adams
Model stores offer third-party ML models and datasets for easy project integration, minimizing coding efforts.
no code implementations • 21 Mar 2022 • Aaditya Bhatia, Ellis E. Eghan, Manel Grichi, William G. Cavanagh, Zhen Ming, Jiang, Bram Adams
However, thus far little is known about the degree of collaboration activity happening on such ML research repositories, in particular regarding (1) the degree to which such repositories receive contributions from forks, (2) the nature of such contributions (i. e., the types of changes), and (3) the nature of changes that are not contributed back to forks, which might represent missed opportunities.
no code implementations • 2 Feb 2022 • Amine Barrak, Bram Adams, Amal Zouaq
Typically, pre-trained language models use transfer-based machine learning models to be fine-tuned for a specific field.
no code implementations • 2 Dec 2020 • Minke Xiu, Ellis E. Eghan, Zhen Ming, Jiang, Bram Adams
Recent advances in Artificial Intelligence (AI), especially in Machine Learning (ML), have introduced various practical applications (e. g., virtual personal assistants and autonomous cars) that enhance the experience of everyday users.
no code implementations • 25 May 2019 • Minke Xiu, Zhen Ming, Jiang, Bram Adams
Recent advances in Artificial Intelligence, especially in Machine Learning (ML), have brought applications previously considered as science fiction (e. g., virtual personal assistants and autonomous cars) into the reach of millions of everyday users.
Software Engineering