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Found 6 papers, 2 papers with code
Evaluation of large language models for assessing code maintainability
Our results show that, controlling for the number of logical lines of codes (LLOC), cross-entropy computed by LLMs is indeed a predictor of maintainability on a class level (the higher the cross-entropy the lower the maintainability).
Badgers: generating data quality deficits with Python
Generating context specific data quality deficits is necessary to experimentally assess data quality of data-driven (artificial intelligence (AI) or machine learning (ML)) applications.
Applications of statistical causal inference in software engineering
This paper reviews existing work in software engineering that applies statistical causal inference methods.
Software Engineering for AI-Based Systems: A Survey
Our results are valuable for: researchers, to quickly understand the state of the art and learn which topics need more research; practitioners, to learn about the approaches and challenges that SE entails for AI-based systems; and, educators, to bridge the gap among SE and AI in their curricula.
Quantitative estimates of impact induced crustal erosion during accretion and its influence on the Sm/Nd ratio of the Earth
Such a late fractionation in the Sm/Nd ratio is unlikely to be responsible for a 20-ppm $^{142}$Nd excess in terrestrial rocks due to the half life of the radiogenic system.
Earth and Planetary Astrophysics Geophysics
Towards Guidelines for Assessing Qualities of Machine Learning Systems
Nowadays, systems containing components based on machine learning (ML) methods are becoming more widespread.
