30 September 2025
There is an increasing need to explain machine learning decisions in an understandable way, even for non-expert users.
In this work, EMERGE partners from the University of Pisa introduce a multi-agent architecture to provide interactive explanations for classification tasks based on a range of machine learning algorithms, so that end-users can obtain answers in natural language. Their architecture is composed of four agents that can convert any classifier into a surrogate Decision Tree around the neighbourhood of a classification instance, which is then translated into a natural language explanation that can be further explored in an interactive way.
Read the paper in the link below.
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