Google's newly released ScreenAI visual language model has made breakthrough progress in multiple understanding tasks, setting a new SOTA record. This model uses the innovative PaLM 2-S automatic data generation method, which effectively improves the diversity and complexity of the data set while ensuring high efficiency. With its multi-modal encoder architecture, ScreenAI can excellently complete text+image-to-text tasks and demonstrate leading performance in tasks such as screen QA, infographics, and document understanding, bringing new developments to the field of visual language models. possibility.
Google recently released the ScreenAI visual language model, which uses PaLM 2-S to automatically generate data, breaking SOTA records for multiple understanding tasks. The model uses a multi-modal encoder architecture to achieve text+image-to-text task solving. Researchers use automated data generation methods to increase the diversity and complexity of data sets while ensuring efficiency. The model achieves leading performance on screen QA, infographics, and document understanding tasks.
The emergence of ScreenAI marks a significant progress in visual language model technology. Its efficient data generation method and leading performance provide a new direction for future AI development. The technology of automatically generating data also provides new ideas and reference for the training of other AI models. We look forward to ScreenAI demonstrating its powerful capabilities in more practical application scenarios.