… Variational Information Bottleneck (VIB) to suppress irrelevant features when fine-tuning on
low-resource … Evaluation on seven low-resource datasets in different tasks shows that our …

… Variational Information Bottleneck (VIB) to suppress irrelevant features when fine-tuning on
low-resource … Evaluation on seven low-resource datasets in different tasks shows that our …

… of labeled data for training or fine-tuning [15], which might pose a … Applying DNN classifiers
to low-resource datasets often leads to … Variational information bottleneck (VIB) addresses the …

… In this paper, we propose to use variational information bottleneck (VIB) method for improving
fine-tuning pre-trained models on small software engineering datasets. It addresses the …

… system improves performance in low-resource and cross-… fine-tuning is conducted using
relatively small amounts of task-specific labeled data. This scheme of pretraining and fine-tuning …

… In this work, we have proposed a novel method to improve low-resource fine-tuning …
The layers are randomly selected during fine-tuning to generate more diverse compressed …

… Variational Information Bottleneck (VIB) to suppress irrelevant features when fine-tuning on
low-resource … Evaluation on seven low-resource datasets in different tasks shows that our …

… model with variational information bottleneck, which makes use of the information especially
… the fine-tuning of pre-training language models in lowresource scenarios (Mahabadi et al.…

… information bottleneck … Information Bottleneck (CIB) to enhance input robustness when
adapting pretrained VLMs to the downstream VQA task. Overall, by minimizing mutual information …

… samples to provide a good direction for parameter optimization in the fine-tuning stage. First,
… Henderson, “Variational information bottleneck for effective low-resource fine-tuning,” in …