Emergent communication aims for a better understanding of human language evolution and
building more efficient representations. We posit that reaching these goals will require …

A fundamental characteristic common to both human vision and natural language is their
compositional nature. Yet despite the performance gains contributed by large vision and …

Lewis signaling games are a class of simple communication games for simulating the
emergence of language. In these games, two agents must agree on a communication …

In the recent shift towards human-centric AI, the need for machines to accurately use natural
language has become increasingly important. While a common approach to achieve this is …

Deep generative models (DGM) are increasingly employed in emergent communication
systems. However, their application in multimodal data contexts is limited. This study …

Simplicial Embeddings (SEM) are representations learned through self-supervised learning
(SSL), wherein a representation is projected into $ L $ simplices of $ V $ dimensions each …

The field of emergent language represents a novel area of research within the domain of
artificial intelligence, particularly within the context of multi-agent reinforcement learning …

The field of emergent communication aims to understand the characteristics of
communication as it emerges from artificial agents solving tasks that require information …

As a sub-discipline of evolutionary and computational linguistics, emergent communication
(EC) studies communication protocols, called emergent languages, arising in simulations …

Computational modeling plays an essential role in the study of language emergence. It aims
to simulate the conditions and learning processes that could trigger the emergence of a …