Adapter-style efficient transfer learning (ETL) has shown excellent performance in the tuning
of vision-language models (VLMs) under the low-data regime, where only a few additional …

With the growing interest in pretrained vision-language models like CLIP, recent research
has focused on adapting these models to downstream tasks. Despite achieving promising …

Detecting out-of-distribution (OOD) samples is crucial for ensuring the safety of machine
learning systems and has shaped the field of OOD detection. Meanwhile, several other …

Artificial intelligence (AI) has significantly advanced Earth sciences, yet its full potential in to
comprehensively modeling Earth's complex dynamics remains unrealized. Geoscience …

Efficient transfer learning (ETL) is receiving increasing attention to adapt large pre-trained
language-vision models on downstream tasks with a few labeled samples. While significant …

Abstract Multi-modal (vision-language) models, such as CLIP, are replacing traditional
supervised pre-training models (eg, ImageNet-based pre-training) as the new generation of …

Sign language video retrieval plays a key role in facilitating information access for the deaf
community. Despite significant advances in video-text retrieval, the complexity and inherent …

Interpreting the decisions of deep learning models has been actively studied since the
explosion of deep neural networks. One of the most convincing interpretation approaches is …

The development of large vision-language models notably CLIP has catalyzed research into
effective adaptation techniques with a particular focus on soft prompt tuning. Conjointly test …

Recent progress in the few-shot adaptation of Vision-Language Models (VLMs) has further
pushed their generalization capabilities at the expense of just a few labeled samples within …