Misinformation detection: Stability of Machine Learning with Limited Labelled Data

Stability of Machine Leargning with Limited Labelled Data

Brano Pecher works on making the job of fact-checkers easier. Within the Kempelen Institute of Intelligent Technologie (KInIT) he helps to automate some parts of the fact-checking process by using machine learning as a part of the international research project CEDMO. The domain of misinformation is characterized by the lack of labels spread across languages and tasks, so KInIT employs approaches for machine learning with limited labelled data that can achieve good transferability. The success of the transfer and the overall stability of performance is affected by many factors. Watch Brano´s explanation on Youtube. 

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