Obscuring Data Contamination Through Translation: Evidence from Arabic Corpora
The research investigated how translating benchmark data into Arabic affects data contamination detection in large language models. The study found that translation can suppress traditional contamination indicators, but models still benefit from exposure to contaminated data, especially those with strong Arabic skills. This necessitates a new method, Translation-Aware Contamination Detection (TACD), which compares signals across translated versions.