@inproceedings{gupta-srinivasaraghavan-2020-explanation,
    title = "Explanation Regeneration via Multi-Hop {ILP} Inference over Knowledge Base",
    author = "Gupta, Aayushee  and
      Srinivasaraghavan, Gopalakrishnan",
    editor = "Ustalov, Dmitry  and
      Somasundaran, Swapna  and
      Panchenko, Alexander  and
      Malliaros, Fragkiskos D.  and
      Hulpuș, Ioana  and
      Jansen, Peter  and
      Jana, Abhik",
    booktitle = "Proceedings of the Graph-based Methods for Natural Language Processing (TextGraphs)",
    month = dec,
    year = "2020",
    address = "Barcelona, Spain (Online)",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2020.textgraphs-1.13/",
    doi = "10.18653/v1/2020.textgraphs-1.13",
    pages = "109--114",
    abstract = "Textgraphs 2020 Workshop organized a shared task on `Explanation Regeneration' that required reconstructing gold explanations for elementary science questions. This work describes our submission to the task which is based on multiple components: a BERT baseline ranking, an Integer Linear Program (ILP) based re-scoring and a regression model for re-ranking the explanation facts. Our system achieved a Mean Average Precision score of 0.3659."
}