# Understanding LSTM -- a tutorial into Long Short-Term Memory Recurrent Neural Networks

arXiv: https://arxiv.org/abs/1909.09586 · HTML: https://mlsanity.com/paper/1909.09586/

## Key facts

- Cited by 103 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Sep 2019.

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## Abstract (arXiv)

Long Short-Term Memory Recurrent Neural Networks (LSTM-RNN) are one of the most powerful dynamic classifiers publicly known. The network itself and the related learning algorithms are reasonably well documented to get an idea how it works. This paper will shed more light into understanding how LSTM-RNNs evolved and why they work impressively well, focusing on the early, ground-breaking publications. We significantly improved documentation and fixed a number of errors and inconsistencies that accumulated in previous publications. To support understanding we as well revised and unified the notation used.