Marco received a Ph.D. in Linguistics from the University of California, Los Angeles. After several experiences in research and industry, he joined the Center for Mind/Brain Sciences at the University of Trento, where he became associate professor. Marco then joined the Facebook AI Research team. He became an ICREA research professor, affiliated with the Linguistics Department of Pompeu Fabra University in Barcelona, while maintaining a joint Facebook affiliation. 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. His current research focuses on a better understanding of artificial neural networks, with a focus on what they can teach us about human language acquisition and processing.
December 23, 2020
There is renewed interest in simulating language emergence among deep neural agents that communicate to jointly solve a task, spurred by the practical aim to develop language-enabled interactive AIs, as well as by theoretical questions about…
Eugene Kharitonov, Rahma Chaabouni, Diane Bouchacourt, Marco Baroni,
December 23, 2020
December 23, 2020
Sequence-processing neural networks led to remarkable progress on many NLP tasks. As a consequence, there has been increasing interest in understanding to what extent they process language as humans do. We aim here to uncover which biases such…
Rahma Chaabouni, Eugene Kharitonov, Alessandro Lazaric, Emmanuel Dupoux, Marco Baroni,
December 23, 2020
December 23, 2020
Lake and Baroni (2018) introduced the SCAN dataset probing the ability of seq2seq models to capture compositional generalizations, such as inferring the meaning of “jump around” 0-shot from the component words. Recurrent networks (RNNs) were…
Roberto Dessi, Marco Baroni,
December 23, 2020