paper-with-me

홈 › Papers

Transformer Ensembles for Sexism Detection

2021-10-29 · Lily Davies, Marta Baldracchi, Carlo Alessandro Borella, Konstantinos Perifanos

This document presents in detail the work done for the sexism detection task at EXIST2021 workshop. Our methodology is built on ensembles of Transformer-based models which are trained on different background and corpora and fine-tuned on the provided dataset from the EXIST2021 workshop. We report accuracy of 0.767 for the binary classification task (task1), and f1 score 0.766, and for the multi-class task (task2) accuracy 0.623 and f1-score 0.535.

📄 PDF Abstract BibTeX arXiv:2110.15905

Code (0)

등록된 구현이 없습니다.

Tasks

Binary Classification

Similar Papers 제목 키워드 기반

AdamR at SemEval-2023 Task 10: Solving the Class Imbalance Problem in Sexism Detection with Ensemble Learning

2023-05-15 · Adam Rydelek, Daryna Dementieva, Georg Groh

The Explainable Detection of Online Sexism task presents the problem of explainable sexism detection through fine-grained categorisation of sexist cases with three subtasks. Our team experimented with different ways to c…

Data AugmentationEnsemble Learning

Stanford MLab at SemEval-2023 Task 10: Exploring GloVe- and Transformer-Based Methods for the Explainable Detection of Online Sexism

2023-05-07 · Hee Jung Choi, Trevor Chow, Aaron Wan, Hong Meng Yam 외

In this paper, we discuss the methods we applied at SemEval-2023 Task 10: Towards the Explainable Detection of Online Sexism. Given an input text, we perform three classification tasks to predict whether the text is sexi…

LCT-1 at SemEval-2023 Task 10: Pre-training and Multi-task Learning for Sexism Detection and Classification

2023-06-08 · Konstantin Chernyshev, Ekaterina Garanina, Duygu Bayram, Qiankun Zheng 외

Misogyny and sexism are growing problems in social media. Advances have been made in online sexism detection but the systems are often uninterpretable. SemEval-2023 Task 10 on Explainable Detection of Online Sexism aims …

Domain AdaptationMulti-Task Learning

Attention at SemEval-2023 Task 10: Explainable Detection of Online Sexism (EDOS)

2023-04-10 · Debashish Roy, Manish Shrivastava

In this paper, we have worked on interpretability, trust, and understanding of the decisions made by models in the form of classification tasks. The task is divided into 3 subtasks. The first task consists of determining…

Classification

Automatic Sexism Detection with Multilingual Transformer Models

2021-06-09 · Mina Schütz, Jaqueline Boeck, Daria Liakhovets, Djordje Slijepčević 외

Sexism has become an increasingly major problem on social networks during the last years. The first shared task on sEXism Identification in Social neTworks (EXIST) at IberLEF 2021 is an international competition in the f…

Binary ClassificationClassificationTask 2Unsupervised Pre-training+1