Large language models (LLMs) are trained on a vast amount of human-written data, but data
providers often remain uncredited. In response to this issue, data valuation (or data …

In recent years, there has been a growing recognition that high-quality training data is
crucial for the performance of machine learning models. This awareness has catalyzed both …

Data fuels machine learning (ML)-rich and high-quality training data is essential to the
success of ML. However, to transform ML from the race among a few large corporations to …

Data is the new oil of the 21st century. The growing trend of trading data for greater welfare
has led to the emergence of data markets. A data market is any mechanism whereby the …

Federated Learning (FL) is a distributed machine learning technique that allows model
training among multiple devices or organizations by sharing training parameters instead of …

Data valuation has emerged as a powerful framework for quantifying each datum's
contribution to the training of a machine learning model. However, it is crucial to recognize …

The acquisition of training data is crucial for machine learning applications. Data markets
can increase the supply of data, particularly in data-scarce domains such as healthcare, by …

As the capabilities of large-scale machine learning (ML) systems rapidly improve, reliable
development & deployment of these systems is increasingly gaining attention. Based on the …

The acquisition of training data is crucial for machine learning applications. Data markets
can increase the supply of data, particularly in data-scarce domains such as healthcare, by …