  Recently, attempting to model texts as graph structure and introducing graph
neural networks to deal with it has become a trend in many NLP research areas.
In this paper, we investigate whether the graph structure is necessary for
multi-hop question answering. Our analysis is centered on HotpotQA. We
construct a strong baseline model to establish that, with the proper use of
pre-trained models, graph structure may not be necessary for multi-hop question
answering. We point out that both graph structure and adjacency matrix are
task-related prior knowledge, and graph-attention can be considered as a
special case of self-attention. Experiments and visualized analysis demonstrate
that graph-attention or the entire graph structure can be replaced by
self-attention or Transformers.
