UCAS-IIE-NLP at SemEval-2023 Task 12: Enhancing Generalization of Multilingual BERT for Low-resource Sentiment Analysis
Year: 2023
Type: conference-paper
Abstract: This paper describes our system designed for SemEval-2023 Task 12: Sentiment analysis for African languages.The challenge faced by this task is the scarcity of labeled data and linguistic resources in low-resource settings.To alleviate these, we propose a generalized multilingual system SACL-XLMR for sentiment analysis on low-resource languages.Specifically, we design a lexicon-based multilingual BERT to facilitate language adaptation and sentimentaware representation learning.Besides, we apply a supervised adversarial contrastive learning technique to learn sentiment-spread structured representations and enhance model generalization.Our system achieved competitive results, largely outperforming baselines on both multilingual and zero-shot sentiment classification subtasks.Notably, the system obtained the 1st rank on the zero-shot classification subtask in the official ranking.Extensive experiments demonstrate the effectiveness of our system.
Authors: Dou Hu, Lingwei Wei, Yaxin Liu, Wei Zhou, Songlin Hu
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4385570064