Hi @Christian,
Yes, your understanding is generally correct about how a BiLSTM (Bidirectional Long Short-Term Memory) layer connects to a sequence input layer in a neural network architecture. When you use a sequence input layer followed by a BiLSTM layer, the input sequence is fed into both the forward and backward LSTM layers of the BiLSTM. Each unit in these LSTM layers processes the entire input sequence (or the entire set of features at each time step) but in opposite directions; the forward LSTM processes the sequence from start to end, while the backward LSTM processes it from end to start.
Regarding the documentation, the specifics of how these connections are implemented can vary depending on the software or framework you're using. Here are links to the documentation for popular frameworks that might help:
