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Found 3 papers, 1 papers with code
Generating Textual Explanations for Machine Learning Models Performance: A Table-to-Text Task
This paper proposes a new natural language generation (NLG) task where neural models are trained to generate textual explanations, analytically describing the classification performance of ML models based on the metrics’ scores reported in the tables.
Fully-Automatic Pipeline for Document Signature Analysis to Detect Money Laundering Activities
Signatures present on corporate documents are often used in investigations of relationships between persons of interest, and prior research into the task of offline signature verification has evaluated a wide range of methods on standard signature datasets.
Finding the Ground-Truth from Multiple Labellers: Why Parameters of the Task Matter
Findings show that both Expectation Maximisation and CrowdTruth are only likely to give an advantage over majority vote under certain parameter conditions, while there are many cases where the methods can be shown to have no major impact.
