Marco Baroni received a PhD in Linguistics from the University of California, Los Angeles, in the year 2000. After several experiences in research and industry, he joined the Center for Mind/Brain Sciences of the University of Trento, where he became associate professor in 2013. In 2016, Marco joined the Facebook Artificial Intelligence Research team. In 2019, he became ICREA research professor, affiliated with the Linguistics Department of Pompeu Fabra University in Barcelona. Marco's work in the areas of multimodal and compositional distributed semantics has received widespread recognition, including a Google Research Award, an ERC Starting Grant, and the ICAI-JAIR best paper prize and the ACL test of time award. Marco's current research focuses on universal linguistic and visual representations in deep-learning-trained artificial neural networks such as large language models. In 2021, he was awarded an ERC Advanced Grant to work on related topics.

While deep-learning-based artificial neural networks have revolutionized science, engineering and our daily life, we still know surprisingly little about how they work. Indeed, they can sometimes behave in completely unexpected ways, exposing weaknesses that can be used for harmful purposes. My current interest lies in opening the black box of modern neural networks, specifically in the domain of language, where I study large language models such as ChatGPT. I am focusing on two main approaches to this challenge. On the one hand, I am studying how large language models react to inputs that are outside their training distribution. On the other, I use tools from probability, linear algebra and information theory to measure the complexity of the internal representations of large language models.