Link of the Paper: https://arxiv.org/pdf/1409.3215.pdf
Main Points:
- Encoder-Decoder Model: Input sequence -> A vector of a fixed dimensionality -> Target sequence.
- A multilayered LSTM: The LSTM did not have difficulty on long sentences.
- Reverse Input: Better performance.
Other Key Points:
- A significant limitation: Despite their flexibility and power, DNNs can only be applied to problems whose inputs and targets can be sensibly encoded with vectors of fixed dimensionality.