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LLM-Rec: Personalized Recommendation via Prompting Large Language Models
Notably, the success of LLM-Rec lies in its prompting strategies, which effectively tap into the language model's comprehension of both general and specific item characteristics.
Cutting-Splicing data augmentation: A novel technology for medical image segmentation
Background: Medical images are more difficult to acquire and annotate than natural images, which results in data augmentation technologies often being used in medical image segmentation tasks.
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