One major reason is that learning long dependencies using gated RNNs may not be effective enough because the gradients are expected to propagate back through inevitably a huge number of utterances and tokens in sequence, which easily leads to the vanishing gradient problem (Bengio et al., 1994).
when the utterance-level LSTM in cLSTM is replaced by features extracted by CNN, i.e., the CNN+cLSTM, the model performs significantly better than cLSTM on long conversations, which further validates that modelling long conversations using only RNN models may not be sufficient.