Pretricaneng a solid opinion or models of Multimodal Foundation (eg clip) depends on the big datasets that can be bad, and have a bad tail. Previous functions have shown prominent results in Agregating Datetats by making samples made. However, they only support characters of the complexity of the heavy (eg any picture or text, but not both different data. In this page, we designate a sign-control of the images, CTRSSYNTH, by Multimodal well-reading. The main idea is to rot the visual images of the image to the basics, enter the specified regulatory policies (eg delete, and take into accounting), and set up additional photos or documents. The role and reorganization feature in Ctrlsynth allows users to manage the integration of information in properly fried effectively by explaining basic policies. CTRTSSYTH Puts the power of beautiful base models such as major languages or models to consult and return the basic characteristics such as such samples are natural. Ctrlsynth is closed loop, training, and standard framework, and making it easy to support different set models. With a wide examination of 31 dataset relating to different tasks of the idea and language language, we show that Ctrlsynththath too improves zero-shots of zero-shots.
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