30 citations · 43 across the 11 of their papers we have counts for
4 papers · 1 filter
When Parameter-efficient Tuning Meets General-purpose Vision-language Models
Yihang Zhai, Haixin Wang, Jianlong Chang +4
Instruction tuning has shown promising potential for developing general-purpose AI capabilities by using large-scale pre-trained models and boosts growing research to integrate mul…
Parameter-efficient Tuning of Large-scale Multimodal Foundation Model
Haixin Wang, Xinlong Yang, Jianlong Chang +5
Driven by the progress of large-scale pre-training, parameter-efficient transfer learning has gained immense popularity across different subfields of Artificial Intelligence. The c…
Exploiting Pseudo Image Captions for Multimodal Summarization
Chaoya Jiang, Rui Xie, Wei Ye +2
Cross-modal contrastive learning in vision language pretraining (VLP) faces the challenge of (partial) false negatives. In this paper, we study this problem from the perspective of…
LION: Implicit Vision Prompt Tuning
Haixin Wang, Jianlong Chang, Xiao Luo +3
Despite recent competitive performance across a range of vision tasks, vision Transformers still have an issue of heavy computational costs. Recently, vision prompt learning has pr…