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Tree-LSTMs are a variant of Long Short Term Memory (LSTM) neural networks.

A traditional LSTM is structured as a linear chain, and displays strong performance on sequence modeling tasks–such as machine translation.

However, some types of data (such as text) are better represented as tree structures instead of sequences. Thus, Tree-LSTMs were introduced by Tai, et al in 2015.