MarsEclipse at SemEval-2023 Task 3: Multi-lingual and Multi-label Framing Detection with Contrastive Learning
Year: 2023
Type: conference-paper
Abstract: This paper describes our system for SemEval-2023 Task 3 Subtask 2 on Framing Detection.We used a multi-label contrastive loss for finetuning large pre-trained language models in a multi-lingual setting, achieving very competitive results: our system was ranked first on the official test set and on the official shared task leaderboard for five of the six languages for which we had training data and for which we could perform fine-tuning.Here, we describe our experimental setup, as well as various ablation studies.The code of our system is available at https://github.com/QishengL/ SemEval2023
Authors: Qisheng Liao, Meiting Lai, Preslav Nakov
Institution: Liaoning University
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4385570023