The main merits of these representation learning based methods are that they do not rely on any linguistic tools and can be applied to different languages or domains.
the memory of these methods, such as Long Short-Term Memory (LSTM) (Hochreiter and Schmidhuber, 1997) and Gated Recurrent Unit (GRU) (Cho et al., 2014) compressing all the external sentences into a fixed-length vector, is typically too small to accurately remember facts from the past, and may lose important details for response generation (Shang et al., 2015).