A new era has dawned with the unveiling of LaVy, a Vietnamese Multimodal Large Language Model (MLLM) that extends the capabilities of language understanding to the nuances of Vietnamese visual language. Developed by Chi Tran and Huong Le Thanh, LaVy signifies a leap towards addressing the scarcity of high-quality multimodal resources in Vietnamese AI research.

• Introduction of LaVy, a state-of-the-art MLLM tailored for Vietnamese visual language tasks.
• Release of LaVy-Bench, a benchmark designed explicitly for evaluating MLLMs on Vietnamese visual language.
• Accessibility of codebases and model weights to encourage collaborative advancements in the field.
• LaVy represents a significant contribution to language model research by catering to a linguistically diverse audience.
• It serves as a catalyst for future developments in the creation of language-specific multimodal models.

This breakthrough has the potential to reshape the AI landscape by providing tools that not only comprehend but can also interact with information in a more culturally and linguistically sensitive manner. The success of LaVy paves the way for more targeted research in underrepresented languages, fostering a more inclusive AI community. Discover more