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Recent work has shown that LSTMs trained on a generic language modelingobjective capture syntax-sensitive generalizations such as long-distance numberagreement. We have however no mechanistic understanding of how they accomplishthis remarkable feat. Some have conjectured it depends on heuristics that donot truly take hierarchical structure into account. We present here a detailedstudy of the inner mechanics of number tracking in LSTMs at the single neuronlevel. We discover that long-distance number information is largely managed bytwo `number units'. Importantly, the behaviour of these units is partiallycontrolled by other units independently shown to track syntactic structure. Weconclude that LSTMs are, to some extent, implementing genuinely syntacticprocessing mechanisms, paving the way to a more general understanding ofgrammatical encoding in LSTMs.

The emergence of number and syntax units in LSTM language models