Abstract Vision-Language Large Models (VLMs) recently become primary backbone of AI,
due to the impressive performance. However, their expensive computation costs, ie …

Diffusion models are acclaimed for generating high-quality and diverse images. However,
their performance notably degrades when trained on data with a long-tailed distribution. For …

As one of the fundamental video tasks in computer vision, Open-Vocabulary Action
Recognition (OVAR) recently gains increasing attention, with the development of vision …

Vision-Language Large Models (VLMs) have become primary backbone of AI, due to the
impressive performance. However, their expensive computation costs, ie, throughput and …

In rapidly evolving field of vision-language models (VLMs), contrastive language-image pre-
training (CLIP) has made significant strides, becoming foundation for various downstream …

Recommendation systems frequently suffer from data sparsity, resulting in less-than-ideal
recommendations. A prominent solution to this problem is Cross-Domain Recommendation …

Recently, Multi-modal Large Language Models (MLLMs) have shown remarkable
effectiveness for multi-modal tasks due to their abilities to generate and understand cross …

For recommender systems in internet platforms, search activities provide additional insights
into user interest through query-click interactions with items, and are thus widely used for …

Live-streaming services have attracted widespread popularity due to their real-time
interactivity and entertainment value. Users can engage with live-streaming authors by …

Cross-Domain Recommendation (CDR) have received widespread attention due to their
ability to utilize rich information across domains. However, most existing CDR methods …