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20182021
most citedCompositional properties of emergent languages in deep learning

4 citations · 6 across the 5 of their papers we have counts for

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14 papers · 1 filter

cs.CL2021

Language Modelling as a Multi-Task Problem

Lucas Weber, Jaap Jumelet, Elia Bruni +1

In this paper, we propose to study language modelling as a multi-task problem, bringing together three strands of research: multi-task learning, linguistics, and interpretability.…

cs.CL2020

The Grammar of Emergent Languages

Oskar van der Wal, Silvan de Boer, Elia Bruni +1

In this paper, we consider the syntactic properties of languages emerged in referential games, using unsupervised grammar induction (UGI) techniques originally designed to analyse…

cs.CL2020

Internal and external pressures on language emergence: least effort, object constancy and frequency

Diana Rodríguez Luna, Edoardo Maria Ponti, Dieuwke Hupkes +1

In previous work, artificial agents were shown to achieve almost perfect accuracy in referential games where they have to communicate to identify images. Nevertheless, the resultin…

cs.CL2020

Co-evolution of language and agents in referential games

Gautier Dagan, Dieuwke Hupkes, Elia Bruni

Referential games offer a grounded learning environment for neural agents which accounts for the fact that language is functionally used to communicate. However, they do not take i…

cs.CL2019

Mastering emergent language: learning to guide in simulated navigation

Mathijs Mul, Diane Bouchacourt, Elia Bruni

To cooperate with humans effectively, virtual agents need to be able to understand and execute language instructions. A typical setup to achieve this is with a scripted teacher whi…

cs.CL2019

Compositionality decomposed: how do neural networks generalise?

Dieuwke Hupkes, Verna Dankers, Mathijs Mul +1

Despite a multitude of empirical studies, little consensus exists on whether neural networks are able to generalise compositionally, a controversy that, in part, stems from a lack…