Does autoregressive mean that the output of our model is combined with current input and this combination acts as input to our model for next time step?


If this is not the case, then what is autoregressive model, if this is the case, then what is done to take care, that one wrong prediction does not destroy all the future time step predictions, as if one wrong prediction is made, then it would get combined with input and act as input for next time step, which would lead to further incorrect predictions.


What is a way to predict variable length sequence, and combine this variable length sequence with input sequence to again make variable length sequence predictions, let us say for pixels?