A decoder LSTM is trained to turn the target sequences into the same sequence but offset by one timestep in the future, a training process called \"teacher forcing\" in this context. It uses as initial state the state vectors from the encoder. Effectively, the decoder learns to generate targets[t+1...] given targets[...t], conditioned on the input sequence.