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Tu et al - Multi-hop Reading Comprehension across Multiple Documents [b0233e2d]

Tags: papers, nlp

  • Tu, Ming, Guangtao Wang, Jing Huang, Yun Tang, Xiaodong He, and Bowen Zhou. “Multi-Hop Reading Comprehension across Multiple Documents by Reasoning over Heterogeneous Graphs.” In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2704–13. Florence, Italy: Association for Computational Linguistics, 2019. doi.org/10.18653/v1/P19-1260.
  • video: vimeo.com/384732193
  • proposes a heterogenous document entity graph with different granularities, uses a graph neural network

  • notes that there are two types of reading comphrension problems:

    1. adding a layer to neural rc models using doc and entity level info
    2. graph neural networks