How does the use of intermediate task fine-tuning (e.g., NLI, QA) between source and target languages impact cross-lingual - Assignee Research (Assignee Research, 2026)
Euphemisms are culturally variable and often ambiguous, posing challenges for language models, especially in low-resource settings. This paper investigates how cross-lingual transfer via sequential fine-tuning affects euphemism detection across five languages: English, Spanish, Chinese, Turkish, and Yoruba. We compare sequential fine-tuning with monolingual and simultaneous fine-tuning using XLM-R and mBERT, analyzing how performance is shaped by language pairings, typological features, and pret
Machine-generated literature synthesis.