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Found 2 papers, 1 papers with code
GIFT: Generative Interpretable Fine-Tuning
We show the output of the first linear layer (i. e., $\omega\cdot \phi$) is surprisingly interpretable, which can play the role of a token-clustering head as a by-product to localize meaningful objects/parts in images for computer vision tasks.
Transforming Transformers for Resilient Lifelong Learning
To our knowledge, it is the first attempt of lifelong learning with ViTs on the challenging VDD benchmark.
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