A system using XLM-RoBERTa, GPT-4 back-translation augmentation, undersampling, and language-specific threshold tuning reports 2-5% F1 gains on multilingual slur reclamation detection.
Popa-Wyatt, Reclamation: Taking back control of words, Grazer Philosophische Studien 97 (2020) 159–176
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KIT-TIP-NLP at MultiPride: Continual Learning with Multilingual Foundation Model
A system using XLM-RoBERTa, GPT-4 back-translation augmentation, undersampling, and language-specific threshold tuning reports 2-5% F1 gains on multilingual slur reclamation detection.