Evaluating Cross-lingual Knowledge Consistency in Code-Mixed vis-a-vis Indian Languages using IndicKLAR
Researchers created INDIKLAR, a benchmark testing how well AI models handle knowledge across native Indian languages and code-mixed text compared to English. The study found that while native language performance is poor, code-mixed inputs significantly reduce this gap, suggesting code-mixing helps models access cross-lingual knowledge more effectively.