ERNIE ViLG

ERNIE is a family of large language models developed primarily for Chinese language processing, but with expanding multilingual capabilities, focusing on improving various NLP and vision-language tasks. Current research emphasizes enhancing model architectures like diffusion models for text-to-image generation and multi-view contrastive learning for improved image-text understanding, as well as exploring knowledge distillation techniques to create smaller, more efficient models. These advancements have led to state-of-the-art results in several areas, including text-to-image synthesis, cross-lingual text-to-speech, and code generation, demonstrating the potential of ERNIE for diverse applications in both research and industry.