Multilingual Context

Multilingual context in natural language processing focuses on developing models capable of understanding and generating text across multiple languages, addressing the significant imbalance in resources available for different languages. Current research emphasizes improving the performance of large language models (LLMs) in low-resource languages, investigating their long-context capabilities in multilingual settings, and exploring techniques like cross-lingual alignment and knowledge editing to mitigate performance disparities. This work is crucial for broadening the accessibility and fairness of AI technologies, impacting applications ranging from machine translation and text-to-speech to hate speech detection and information retrieval across diverse linguistic communities.