Given the appropriate weights for the various gates, an LSTM cell accepts three inputs at each time step: the memory cell internal state (context vector) and the hidden state from the previous time step, along with the current input vector. The cell then produces updated memory cell internal state and hidden state vectors as output. Crucially, only the hidden state is passed into the output layer or forwarded to subsequent layers in a stacked RNN, while the memory cell internal state remains entirely internal to the LSTM unit and is never exposed outside it.