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Found 3 papers, 3 papers with code
Preventing Zero-Shot Transfer Degradation in Continual Learning of Vision-Language Models
To address this challenge, we propose a novel method ZSCL to prevent zero-shot transfer degradation in the continual learning of vision-language models in both feature and parameter space.
InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data Pruning
To solve this problem, we propose \textbf{InfoBatch}, a novel framework aiming to achieve lossless training acceleration by unbiased dynamic data pruning.
CowClip: Reducing CTR Prediction Model Training Time from 12 hours to 10 minutes on 1 GPU
Our experiments show that previous scaling rules fail in the training of CTR prediction neural networks.
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