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Found 4 papers, 1 papers with code
On the Readiness of Scientific Data for a Fair and Transparent Use in Machine Learning
To ensure the fairness and trustworthiness of machine learning (ML) systems, recent legislative initiatives and relevant research in the ML community have pointed out the need to document the data used to train ML models.
Towards the Automatic Generation of Conversational Interfaces to Facilitate the Exploration of Tabular Data
Tabular data is the most common format to publish and exchange structured data online.
A domain-specific language for describing machine learning datasets
So far, these proposals are mostly high-level guidelines described in natural language and, as such, they are difficult to formalize and apply to particular datasets.
The Present and Future of Bots in Software Engineering
We are witnessing a massive adoption of software engineering bots, applications that react to events triggered by tools and messages posted by users and run automated tasks in response, in a variety of domains.
