… neuralese messages by translating them. In this work, we present a simple technique for
inducing a dictionary that maps between neuralese … task of machine translation between pairs of …

… neuralese messages by translating them. In this work, we present a simple technique for
inducing a dictionary that maps between neuralese … task of machine translation between pairs of …

… We describe a rationalization technique that uses neural machine translation to translate
internal state-action representations of an autonomous agent into natural language. We …

… and translate a foreign language emerges as a means to achieve shared goals. The emergent
translation … We find that the ability to translate foreign languages emerges as a means to …

This dissertation explores the use of linguistic structure to inform the structure and
parameterization of machine learning models for language processing and other applications. We …

What is the relation between the material, conventional symbol structures that we encounter
in the spoken and written word, and human thought? A common assumption, that structures …

Rapid progress in Neural Machine Translation (NMT) systems over the last few years has
focused primarily on improving translation quality, and as a secondary focus, improving …

… translation mechanism from natural language to EC. Using a dataset of images with
naturallanguage labels, one can construct a translation … -squares linear “translator” model to map …

Rapid progress in Neural Machine Translation (NMT) systems over the last few years has
been driven primarily towards improving translation quality, and as a secondary focus, …

By capturing statistical patterns in large corpora, machine learning has enabled significant
advances in natural language processing, including in machine translation, question …