June 2023

Improving inverse abstraction based neural network verification using automated machine learning techniques

Matthias könig PhD at Leiden University Abstract: This project seeks to advance the state of the art in formal neural network verification. Formal neural network verification methods check whether a trained neural network, for example an image classifier, satisfies certain properties or guarantees regarding its behaviour, such as correctness, robustness, or safety, under various inputs […]

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Towards Stable and Robust Learning with Limited Labelled Data: Investigating the Impact of Data Choice

Branislav Pecher PhD at Kempelen Institute of Intelligent Technologies, member of Slovak.AI Abstract: Learning with limited labelled data, such as meta-learning, transfer learning or in-context learning, aims to effectively train a model using only a small amount of labelled samples. However, there is still limited understanding of the required settings or characteristics for these approaches

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BEYOND CHATGPT: Europe needs to act now to ensure technological sovereignty in Next-Generation AI – Call for Action following the EU Parliament Meeting

On May 25th, 2023 TAILOR made its contribution to the event Beyond ChatGPT: How can Europe get in front of the pack on Generative AI Models?, organised by a broad consortium of European projects and Institutions: the HumanE-AI-Net European Network of Centres of Excellence in Artificial Intelligence, the International Research Centre on Artificial Intelligence (IRCAI) under the

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