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Found 8 papers, 3 papers with code
A State-of-the-practice Release-readiness Checklist for Generative AI-based Software Products
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.
Exploring the Impact of the Output Format on the Evaluation of Large Language Models for Code Translation
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.
An Empirical Study of Challenges in Machine Learning Asset Management
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.
The State of Documentation Practices of Third-party Machine Learning Models and Datasets
Model stores offer third-party ML models and datasets for easy project integration, minimizing coding efforts.
Towards a Change Taxonomy for Machine Learning Systems
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.
Toward a traceable, explainable, and fairJD/Resume recommendation system
Typically, pre-trained language models use transfer-based machine learning models to be fine-tuned for a specific field.
Empirical Study on the Software Engineering Practices in Open Source ML Package Repositories
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.
An Exploratory Study on Machine Learning Model Stores
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
