@inproceedings{luo-tang-2020-funny3,
    title = "Funny3 at {S}em{E}val-2020 Task 7: Humor Detection of Edited Headlines with {LSTM} and {TFIDF} Neural Network System",
    author = "Luo, Xuefeng  and
      Tang, Kuan",
    editor = "Herbelot, Aurelie  and
      Zhu, Xiaodan  and
      Palmer, Alexis  and
      Schneider, Nathan  and
      May, Jonathan  and
      Shutova, Ekaterina",
    booktitle = "Proceedings of the Fourteenth Workshop on Semantic Evaluation",
    month = dec,
    year = "2020",
    address = "Barcelona (online)",
    publisher = "International Committee for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2020.semeval-1.132/",
    doi = "10.18653/v1/2020.semeval-1.132",
    pages = "1013--1018",
    abstract = "This paper presents a neural network system where we participate in the first task of SemEval-2020 shared task 7 ``Assessing the Funniness of Edited News Headlines''. Our target is to create to neural network model that can predict the funniness of edited headlines. We build our model using a combination of LSTM and TF-IDF, then a feed-forward neural network. The system manages to slightly improve RSME scores regarding our mean score baseline."
}