19 research outputs found
Emergent Language Generalization and Acquisition Speed are not tied to Compositionality
Studies of discrete languages emerging when neural agents communicate to
solve a joint task often look for evidence of compositional structure. This
stems for the expectation that such a structure would allow languages to be
acquired faster by the agents and enable them to generalize better. We argue
that these beneficial properties are only loosely connected to
compositionality. In two experiments, we demonstrate that, depending on the
task, non-compositional languages might show equal, or better, generalization
performance and acquisition speed than compositional ones. Further research in
the area should be clearer about what benefits are expected from
compositionality, and how the latter would lead to them