HHU at SemEval-2023 Task 3: An Adapter-based Approach for News Genre Classification
Fabian Billert, Stefan Conrad
The 17th International Workshop on Semantic Evaluation (SemEval-2023) Task 3: detecting the category, the framing, and the persuasion techniques in online news in a multi-lingual setup Paper
TLDR:
This paper describes our approach for Subtask 1 of Task 3 at SemEval-2023. In this subtask, task participants were asked to classify multilingual news articles for one of three classes: Reporting, Opinion Piece or Satire. By training an AdapterFusion layer composing the task-adapters from different
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Abstract:
This paper describes our approach for Subtask 1 of Task 3 at SemEval-2023. In this subtask, task participants were asked to classify multilingual news articles for one of three classes: Reporting, Opinion Piece or Satire. By training an AdapterFusion layer composing the task-adapters from different languages, we successfully combine the language-exclusive knowledge and show that this improves the results in nearly all cases, including in zero-shot scenarios.