Modern language models (LMs) have been successfully employed in source code
generation and understanding, leading to a significant increase in research focused on …

Abstract Machine learning (ML) has recently enabled many modeling tasks in design,
manufacturing, and condition monitoring due to its unparalleled learning ability using …

External audits of AI systems are increasingly recognized as a key mechanism for AI
governance. The effectiveness of an audit, however, depends on the degree of access …

This is the interim publication of the first International Scientific Report on the Safety of
Advanced AI. The report synthesises the scientific understanding of general-purpose AI--AI …

Data integration has been extensively studied by the data management community and is a
core task in the data pre-processing step of ML pipelines. When the integrated data is used …

Entity matching (EM) is a challenging problem studied by different communities for over half
a century. Algorithmic fairness has also become a timely topic to address machine bias and …

Fairness in machine learning (ML) emerges as a critical concern as AI systems increasingly
influence diverse aspects of society, from healthcare decisions to legal judgments. Many …

The integration of Artificial Intelligence (AI) into education has transformative potential,
providing tailored learning experiences and creative instructional approaches. However, the …

AI-driven decision-making systems are becoming instrumental in the public sector, with
applications spanning areas like criminal justice, social welfare, financial fraud detection …

Deep neural networks often learn unintended bias during training, which might have harmful
effects when deployed in realworld settings. This work surveys 214 papers related to …