Referential communication in heterogeneous communities of pre-trained visual deep networks
As large pre-trained image-processing neural networks are being embedded in autonomous
agents such as self-driving cars or robots, the question arises of how such systems can
communicate with each other about the surrounding world, despite their different
architectures and training regimes. As a first step in this direction, we systematically explore
the task of\textit {referential communication} in a community of heterogeneous state-of-the-
art pre-trained visual networks, showing that they can develop, in a self-supervised way, a …
agents such as self-driving cars or robots, the question arises of how such systems can
communicate with each other about the surrounding world, despite their different
architectures and training regimes. As a first step in this direction, we systematically explore
the task of\textit {referential communication} in a community of heterogeneous state-of-the-
art pre-trained visual networks, showing that they can develop, in a self-supervised way, a …
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