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Found 2 papers, 1 papers with code
Multi-Attribute Vision Transformers are Efficient and Robust Learners
Since their inception, Vision Transformers (ViTs) have emerged as a compelling alternative to Convolutional Neural Networks (CNNs) across a wide spectrum of tasks.
Align Your Prompts: Test-Time Prompting with Distribution Alignment for Zero-Shot Generalization
The promising zero-shot generalization of vision-language models such as CLIP has led to their adoption using prompt learning for numerous downstream tasks.
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