Is Graph Structure Necessary for Multi-hop Question Answering?
Nan Shao, Yiming Cui, Ting Liu, Shijin Wang, Guoping Hu · 2020
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 graphattention 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.