Cross Lingual Generation

Cross-lingual generation focuses on training language models to generate text in multiple languages, aiming to overcome limitations of existing models that struggle with consistent and accurate multilingual output. Current research emphasizes improving the robustness and accuracy of these models across diverse languages, particularly low-resource ones, often employing techniques like multilingual fine-tuning, prompt engineering, and multimodal augmentation with data such as images and captions to enhance generation quality. This field is crucial for bridging language barriers in applications like news translation, multilingual summarization, and cross-cultural communication, impacting both the development of more inclusive AI systems and the accessibility of information globally.