This paper proposes a runtime system called REA that enables the coordination of fast, reactive policies (like those used in vision-language models) with slower, deliberative brain models, allowing them to work together effectively. Practitioners might care about REA because it can improve the performance and efficiency of embodied systems like robots.
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This paper shows that foundation models can be trained with a single algorithm, which can improve the accuracy-compute tradeoff and task coverage. Practitioners might care because this approach can simplify and streamline the training process for foundation models.
This paper introduces a new AI model called Venus-DefakerOne2 that can detect a wide range of fake images, videos, and documents, and is useful for developers who need to build robust anti-forgery systems.