Multilingual Lm

Multilingual language models (MLMs) aim to build language understanding and generation capabilities across multiple languages, often leveraging transformer architectures. Current research focuses on improving MLM performance by optimizing data composition for training, investigating the relationship between model architecture and learnability across languages, and mitigating biases stemming from imbalanced training data and cross-lingual interference. These advancements are crucial for creating more robust and equitable natural language processing tools applicable to a wider range of languages and downstream tasks, impacting fields like machine translation, question answering, and cross-cultural communication.