John Boy Walton at SemEval-2023 Task 5: An Ensemble Approach to Spoiler Classification and Retrieval for Clickbait Spoiling

被引:0
|
作者
Shmalts, Maksim [1 ]
机构
[1] Univ Tubingen, Dept Linguist, Tubingen, Germany
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Clickbait spoiling is a task of generating or retrieving a fairly short text with a purpose to satisfy curiosity of a content consumer without their addressing to the document linked to a clickbait post or headline. In this paper we introduce an ensemble approach to clickbait spoiling task at SemEval-2023. The tasks consists of spoiler classification and retrieval on Webis-Clickbait-22 dataset. We show that such an ensemble solution is quite successful at classification, whereas it might perform poorly at retrieval with no additional features. In conclusion we outline our thoughts on possible directions to improving the approach and shape a set of suggestions to the said features.
引用
收藏
页码:2100 / 2106
页数:7
相关论文
共 33 条
  • [1] SemEval-2023 Task 5: Clickbait Spoiling
    Froebe, Maik
    Gollub, Tim
    Stein, Benno
    Hagen, Matthias
    Potthast, Martin
    17TH INTERNATIONAL WORKSHOP ON SEMANTIC EVALUATION, SEMEVAL-2023, 2023, : 2275 - 2286
  • [2] Matt Bai at SemEval-2023 Task 5: Clickbait spoiler classification via BERT
    Tailor, Nukit
    Mamidi, Radhika
    17TH INTERNATIONAL WORKSHOP ON SEMANTIC EVALUATION, SEMEVAL-2023, 2023, : 1067 - 1068
  • [3] Brooke-English at SemEval-2023 Task 5: Clickbait Spoiling
    Tang, Shirui
    17TH INTERNATIONAL WORKSHOP ON SEMANTIC EVALUATION, SEMEVAL-2023, 2023, : 64 - 76
  • [4] Francis Wilde at SemEval-2023 Task 5: Clickbait Spoiler Type Identification with Transformers
    Indurthi, Vijayasaradhi
    Varma, Vasudeva
    17TH INTERNATIONAL WORKSHOP ON SEMANTIC EVALUATION, SEMEVAL-2023, 2023, : 1890 - 1893
  • [5] Clark Kent at SemEval-2023 Task 5: SVMs, Transformers, and Pixels for Clickbait Spoiling
    Mihalcea, Dragos-Stefan
    Nisioi, Sergiu
    17TH INTERNATIONAL WORKSHOP ON SEMANTIC EVALUATION, SEMEVAL-2023, 2023, : 1204 - 1212
  • [6] Sabrina Spellman at SemEval-2023 Task 5: Discover the Shocking Truth Behind this Composite Approach to Clickbait Spoiling!
    Birkenheuer, Simon
    Drechsel, Jonathan
    Justen, Paul
    Poehlmann, Jimmy
    Gonsior, Julius
    Reusch, Anja
    17TH INTERNATIONAL WORKSHOP ON SEMANTIC EVALUATION, SEMEVAL-2023, 2023, : 969 - 977
  • [7] Billy-Batson at SemEval-2023 Task 5: An Information Condensation based System for Clickbait Spoiling
    Sharma, Anubhav
    Joshi, Sagar
    Abhishek, Tushar
    Mamidi, Radhika
    Varma, Vasudeva
    17TH INTERNATIONAL WORKSHOP ON SEMANTIC EVALUATION, SEMEVAL-2023, 2023, : 1878 - 1889
  • [8] Walter Burns at SemEval-2023 Task 5: NLP-CIMAT - Leveraging Model Ensembles for Clickbait Spoiling
    Villa-Cueva, Emilio
    Vallejo-Aldana, Daniel
    Sanchez-Vega, Fernando
    Lopez-Monroy, Adrian Pastor
    17TH INTERNATIONAL WORKSHOP ON SEMANTIC EVALUATION, SEMEVAL-2023, 2023, : 693 - 699
  • [9] TohokuNLP at SemEval-2023 Task 5: Clickbait Spoiling via Simple Seq2seq Generation and Ensembling
    Kurita, Hiroto
    Ito, Ikumi
    Funayama, Hiroaki
    Sasaki, Shota
    Moriya, Shoji
    Ye Mengyu
    Kokuta, Kazuma
    Hatakeyama, Ryujin
    Sone, Shusaku
    Inui, Kentaro
    17TH INTERNATIONAL WORKSHOP ON SEMANTIC EVALUATION, SEMEVAL-2023, 2023, : 1756 - 1762
  • [10] Mr-wallace at SemEval-2023 Task 5: Novel Clickbait Spoiling Algorithm Using Natural Language Processing
    Saravanan, Vineet
    Wilson, Steven
    17TH INTERNATIONAL WORKSHOP ON SEMANTIC EVALUATION, SEMEVAL-2023, 2023, : 1625 - 1629