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@article{156962,
        author = {AFREEN SULTANA},
        title = {A SURVEY ON MULTI-HOP READING COMPREHENSION},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {5},
        pages = {873-878},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=156962},
        abstract = {Multi-hop Reading Comprehension (MHRC) is a dynamic field of Natural Language Processing (NLP) with real-world applications. The great advancement in this field in recent years has been largely due to the emergence of large databases and in-depth learning. At present, many MHRC models have already surpassed human performance in limited data sets despite the huge gap between existing MHRC models and a real understanding of human-level learning. This highlights the need to improve existing data sets, analytical metrics, and models in order to move current MHRC models to a “real” understanding. To address the current lack of comprehensive survey of existing MRC activities, analytical metrics, and data sets, here, (1) we analyzed MHRC activities and data sets (2) summarized eight different but effective strategies for learning comprehension.},
        keywords = {Multi-hop Reading Comprehension (MHRC), WikiHop, HotpotQA},
        month = {},
        }