120 citations · 348 across the 9 of their papers we have counts for
9 papers
Emergent Multi-Agent Communication in the Deep Learning Era
Angeliki Lazaridou, Marco Baroni
The ability to cooperate through language is a defining feature of humans. As the perceptual, motory and planning capabilities of deep artificial networks increase, researchers are…
Focus on What's Informative and Ignore What's not: Communication Strategies in a Referential Game
Roberto Dessì, Diane Bouchacourt, Davide Crepaldi +1
Research in multi-agent cooperation has shown that artificial agents are able to learn to play a simple referential game while developing a shared lexicon. This lexicon is not easy…
The emergence of number and syntax units in LSTM language models
Yair Lakretz, German Kruszewski, Theo Desbordes +3
Recent work has shown that LSTMs trained on a generic language modeling objective capture syntax-sensitive generalizations such as long-distance number agreement. We have however n…
Linguistic generalization and compositionality in modern artificial neural networks
Marco Baroni
In the last decade, deep artificial neural networks have achieved astounding performance in many natural language processing tasks. Given the high productivity of language, these m…
Human few-shot learning of compositional instructions
Brenden M. Lake, Tal Linzen, Marco Baroni
People learn in fast and flexible ways that have not been emulated by machines. Once a person learns a new verb "dax," he or she can effortlessly understand how to "dax twice," "wa…
CommAI: Evaluating the first steps towards a useful general AI
Marco Baroni, Armand Joulin, Allan Jabri +4
With machine learning successfully applied to new daunting problems almost every day, general AI starts looking like an attainable goal. However, most current research focuses inst…