This AI Paper from UC Santa Cruz and the University of Edinburgh Introduces CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions

Web-crawled image-text datasets are critical for training vision-language models, enabling advancements in tasks such as image captioning and visual question answering.  However, these datasets often suffer from noise and low quality, with inconsistent associations between images and text that limit the capabilities of the models. This limitation prevents achieving strong and accurate results, particularly in […]

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