تقرير
AustroTox: A Dataset for Target-Based Austrian German Offensive Language Detection
| العنوان: | AustroTox: A Dataset for Target-Based Austrian German Offensive Language Detection |
|---|---|
| المؤلفون: | Pachinger, Pia, Goldzycher, Janis, Planitzer, Anna Maria, Kusa, Wojciech, Hanbury, Allan, Neidhardt, Julia |
| سنة النشر: | 2024 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Computers and Society, I.2.7 |
| الوصف: | Model interpretability in toxicity detection greatly profits from token-level annotations. However, currently such annotations are only available in English. We introduce a dataset annotated for offensive language detection sourced from a news forum, notable for its incorporation of the Austrian German dialect, comprising 4,562 user comments. In addition to binary offensiveness classification, we identify spans within each comment constituting vulgar language or representing targets of offensive statements. We evaluate fine-tuned language models as well as large language models in a zero- and few-shot fashion. The results indicate that while fine-tuned models excel in detecting linguistic peculiarities such as vulgar dialect, large language models demonstrate superior performance in detecting offensiveness in AustroTox. We publish the data and code. Comment: Accepted to Findings of the Association for Computational Linguistics: ACL 2024 |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2406.08080 |
| رقم الأكسشن: | edsarx.2406.08080 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |