9 citations · 27 across the 6 of their papers we have counts for
6 papers
RoRA: Role-Oriented Regional Allocation for Visual Token Pruning in MLLMs
Qiyanhui Lu, Han Wu, Rongjian Xu +6
Multimodal large language models (MLLMs) encode images as long visual token sequences, making prefilling and KV-cache storage expensive. Existing training-free pruning methods sele…
GeminiFusion: Efficient Pixel-wise Multimodal Fusion for Vision Transformer
Ding Jia, Jianyuan Guo, Kai Han +4
Cross-modal transformers have demonstrated superiority in various vision tasks by effectively integrating different modalities. This paper first critiques prior token exchange meth…
Data-efficient Large Vision Models through Sequential Autoregression
Jianyuan Guo, Zhiwei Hao, Chengcheng Wang +5
Training general-purpose vision models on purely sequential visual data, eschewing linguistic inputs, has heralded a new frontier in visual understanding. These models are intended…
FastMIM: Expediting Masked Image Modeling Pre-training for Vision
Jianyuan Guo, Kai Han, Han Wu +3
The combination of transformers and masked image modeling (MIM) pre-training framework has shown great potential in various vision tasks. However, the pre-training computational bu…
Hierarchical Relational Learning for Few-Shot Knowledge Graph Completion
Han Wu, Jie Yin, Bala Rajaratnam +1
Knowledge graphs (KGs) are powerful in terms of their inference abilities, but are also notorious for their incompleteness and long-tail distribution of relations. To address these…
Hire-MLP: Vision MLP via Hierarchical Rearrangement
Jianyuan Guo, Yehui Tang, Kai Han +5
Previous vision MLPs such as MLP-Mixer and ResMLP accept linearly flattened image patches as input, making them inflexible for different input sizes and hard to capture spatial inf…