hhuEDOS at SemEval-2023 Task 10: Explainable Detection of Online Sexism (EDOS) - Binary Sexism Detection (Subtask A)

被引：0
|
作者：
Petersen, Wiebke [1 ]
Diem-Ly Tran [1 ]
Wroblewitz, Marion [1 ]
机构：
[1] Heinrich Heine Univ Dusseldorf, Dusseldorf, Germany
来源：
17TH INTERNATIONAL WORKSHOP ON SEMANTIC EVALUATION, SEMEVAL-2023 | 2023年
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：
In this paper, we describe our contribution to the SemEval-2023 Task 10 (Subtask A), a shared task on detecting and predicting sexist language. The dataset consists of labeled sexist and non-sexist data targeted towards women acquired from both Reddit and Gab. We present and compare several approaches we experimented with and our final submitted model. Additional error analysis is given to recognize challenges we dealt with in our process. A total of 84 teams participated. Our model ranks 55th overall in Subtask A of the shared task.
引用
收藏
页码：1476 / 1482
页数：7
相关论文
共 50 条
  • [31] Lexicools at SemEval-2023 Task 10: Sexism Lexicon Construction via XAI
    Nakwijit, Pakawat
    Samir, Mahmoud
    Purver, Matthew
    17TH INTERNATIONAL WORKSHOP ON SEMANTIC EVALUATION, SEMEVAL-2023, 2023, : 23 - 43
  • [32] PingAnLifeInsurance at SemEval-2023 Task 10: Using Multi-Task Learning to Better Detect Online Sexism
    Zhou, Mengyuan
    Hou, Xiaolong
    Jin, Meizhi
    Du, Xiyang
    Chen, Cheng
    Jiang, Lianxin
    Li, Jianyu
    Wei, Zhenggang
    17TH INTERNATIONAL WORKSHOP ON SEMANTIC EVALUATION, SEMEVAL-2023, 2023, : 2188 - 2192
  • [33] DH-FBK at SemEval-2023 Task 10: Multi-Task Learning with Classifier Ensemble Agreement for Sexism Detection
    Leonardelli, Elisa
    Casula, Camilla
    17TH INTERNATIONAL WORKSHOP ON SEMANTIC EVALUATION, SEMEVAL-2023, 2023, : 1894 - 1905
  • [34] HITSZQ at SemEval-2023 Task 10: Category-aware Sexism Detection Model with Self-training Strategy
    Yao, Ziyi
    Chai, Heyan
    Cui, Jinhao
    Tang, Siyu
    Liao, Qing
    17TH INTERNATIONAL WORKSHOP ON SEMANTIC EVALUATION, SEMEVAL-2023, 2023, : 934 - 940
  • [35] MarSan at SemEval-2023 Task 10: Can Adversarial Training with help of a Graph Convolutional Network Detect Explainable Sexism?
    Tavan, Ehsan
    Najafi, Maryam
    17TH INTERNATIONAL WORKSHOP ON SEMANTIC EVALUATION, SEMEVAL-2023, 2023, : 1011 - 1020
  • [36] LCT-1 at SemEval-2023 Task 10: Pre-training and Multi-task Learning for Sexism Detection and Classification
    Chernyshev, Konstantin
    Garanina, Ekaterina
    Bayram, Duygu
    Zheng, Qiankun
    Edman, Lukas
    17TH INTERNATIONAL WORKSHOP ON SEMANTIC EVALUATION, SEMEVAL-2023, 2023, : 1573 - 1581
  • [37] FiRC at SemEval-2023 Task 10: Fine-grained Classification of Online Sexism Content using DeBERTa
    Hassan, Fadi
    Bouchekif, Abdessalam
    Aransa, Walid
    17TH INTERNATIONAL WORKSHOP ON SEMANTIC EVALUATION, SEMEVAL-2023, 2023, : 1824 - 1832
  • [38] Brainstormers_msec at SemEval-2023 Task 10: Detection of sexism related comments in social media using deep learning
    Mahibha, C. Jerin
    Swaathi, C. M.
    Jeevitha, R.
    Martina, R. Princy
    Thenmozhi, Durairaj
    17TH INTERNATIONAL WORKSHOP ON SEMANTIC EVALUATION, SEMEVAL-2023, 2023, : 1114 - 1120
  • [39] MilaNLP at SemEval-2023 Task 10: Ensembling Domain-Adapted and Regularized Pretrained Language Models for Robust Sexism Detection
    Curry, Amanda Cercas
    Attanasio, Giuseppe
    Nozza, Debora
    Hovy, Dirk
    17TH INTERNATIONAL WORKSHOP ON SEMANTIC EVALUATION, SEMEVAL-2023, 2023, : 2067 - 2074
  • [40] HULAT at SemEval-2023 Task 10: Data Augmentation for Pre-trained Transformers Applied to the Detection of Sexism in Social Media
    Segura-Bedmar, Isabel
    17TH INTERNATIONAL WORKSHOP ON SEMANTIC EVALUATION, SEMEVAL-2023, 2023, : 184 - 192
12345