50 citations · 67 across the 4 of their papers we have counts for
8 papers · 1 filter
Unsupervised and Distributional Detection of Machine-Generated Text
Matthias Gallé, Jos Rozen, Germán Kruszewski +1
The power of natural language generation models has provoked a flurry of interest in automatic methods to detect if a piece of text is human or machine-authored. The problem so far…
Evaluating Online Continual Learning with CALM
Germán Kruszewski, Ionut-Teodor Sorodoc, Tomas Mikolov
Online Continual Learning (OCL) studies learning over a continuous data stream without observing any single example more than once, a setting that is closer to the experience of hu…
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…
Cooperative Learning of Disjoint Syntax and Semantics
Serhii Havrylov, Germán Kruszewski, Armand Joulin
There has been considerable attention devoted to models that learn to jointly infer an expression's syntactic structure and its semantics. Yet, \citet{NangiaB18} has recently shown…
The Fast and the Flexible: training neural networks to learn to follow instructions from small data
Rezka Leonandya, Elia Bruni, Dieuwke Hupkes +1
Learning to follow human instructions is a long-pursued goal in artificial intelligence. The task becomes particularly challenging if no prior knowledge of the employed language is…
Learning compositionally through attentive guidance
Dieuwke Hupkes, Anand Singh, Kris Korrel +2
While neural network models have been successfully applied to domains that require substantial generalisation skills, recent studies have implied that they struggle when solving th…