The recently proposed Transformer adopted the self-attention mechanism which could implicitly capture inter-word dependencies in an unsupervised way (Vaswani et al., 2017).
separately processing H and U n then combine their attention with a learned λ performs better than treating the whole dialogue tokens as s single input, though the improvement is less significant compared with previous two mentions.