Xu at SemEval-2022 Task 4: Pre-BERT Neural Network Methods vs Post-BERT RoBERTa Approach for Patronizing and Condescending Language Detection
–arXiv.org Artificial Intelligence
This paper describes my participation in the SemEval-2022 Task 4: Patronizing and Condescending Language Detection. I participate in both subtasks: Patronizing and Condescending Language (PCL) Identification and Patronizing and Condescending Language Categorization, with the main focus put on subtask 1. The experiments compare pre-BERT neural network (NN) based systems against post-BERT pretrained language model RoBERTa. This research finds NN-based systems in the experiments perform worse on the task compared to the pretrained language models. The top-performing RoBERTa system is ranked 26 out of 78 teams (F1-score: 54.64) in subtask 1, and 23 out of 49 teams (F1-score: 30.03) in subtask 2.
arXiv.org Artificial Intelligence
Nov-13-2022
- Country:
- Africa
- Ghana (0.04)
- Kenya (0.04)
- Nigeria (0.04)
- South Africa (0.04)
- Tanzania (0.04)
- Asia
- Europe
- Germany > Baden-Württemberg
- Tübingen Region > Tübingen (0.14)
- Ireland (0.04)
- Germany > Baden-Württemberg
- North America
- Canada (0.04)
- Jamaica (0.04)
- United States (0.04)
- Oceania > Australia (0.04)
- Africa
- Genre:
- Research Report (0.50)
- Technology: