LaVy: Vietnamese Multimodal Large Language Model
This addresses the problem of limited progress in Vietnamese multimodal AI for researchers and developers, though it is incremental as it adapts existing MLLM paradigms to a specific language.
The authors tackled the lack of high-quality multimodal resources for Vietnamese by introducing LaVy, a state-of-the-art Vietnamese Multimodal Large Language Model, and LaVy-Bench, a benchmark for evaluating such models on Vietnamese visual language tasks.
Large Language Models (LLMs) and Multimodal Large language models (MLLMs) have taken the world by storm with impressive abilities in complex reasoning and linguistic comprehension. Meanwhile there are plethora of works related to Vietnamese Large Language Models, the lack of high-quality resources in multimodality limits the progress of Vietnamese MLLMs. In this paper, we pioneer in address this by introducing LaVy, a state-of-the-art Vietnamese MLLM, and we also introduce LaVy-Bench benchmark designated for evaluating MLLMs's understanding on Vietnamese visual language tasks. Our project is public at https://github.com/baochi0212/LaVy