@inproceedings{reddy-biswal-2020-iiitbh,
    title = "{IIITBH} at {WNUT}-2020 Task 2: Exploiting the best of both worlds",
    author = "Reddy, Saichethan  and
      Biswal, Pradeep",
    editor = "Xu, Wei  and
      Ritter, Alan  and
      Baldwin, Tim  and
      Rahimi, Afshin",
    booktitle = "Proceedings of the Sixth Workshop on Noisy User-generated Text (W-NUT 2020)",
    month = nov,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest_wac_2008/2020.wnut-1.46/",
    doi = "10.18653/v1/2020.wnut-1.46",
    pages = "342--346",
    abstract = "In this paper, we present IIITBH team`s effort to solve the second shared task of the 6th Workshop on Noisy User-generated Text (W-NUT)i.e Identification of informative COVID-19 English Tweets. The central theme of the task is to develop a system that automatically identify whether an English Tweet related to the novel coronavirus (COVID-19) is Informative or not. Our approach is based on exploiting semantic information from both max pooling and average pooling, to this end we propose two models."
}