1 citations · 2 across the 5 of their papers we have counts for
8 papers
ACPruner: Visual Token Pruning as Biased Attention Coverage Maximization in LVLMs
Xu Li, Yuxuan Liang, Yi Zheng +6
Large Vision-Language Models (LVLMs) face significant computational inefficiencies caused by the large number of visual tokens. Existing visual token pruning methods mainly focus o…
CAR-VLA: Complexity-Aware and Risk-Adaptive Reasoning for Autonomous Driving
Xiaolei Chen, Zhuolin He, Yuxuan Liang +14
Existing adaptive reasoning methods for driving Vision-Language-Action (VLA) models primarily focus on whether to reason, overlooking how reasoning should differ across driving sit…
Pyramid Token Pruning for High-Resolution Large Vision-Language Models via Region, Token, and Instruction-Guided Importance
Yuxuan Liang, Xu Li, Xiaolei Chen +4
Large Vision-Language Models (LVLMs) have recently demonstrated strong multimodal understanding, yet their fine-grained visual perception is often constrained by low input resoluti…
HERO: Rethinking Visual Token Early Dropping in High-Resolution Large Vision-Language Models
Xu Li, Yuxuan Liang, Xiaolei Chen +4
By cropping high-resolution images into local tiles and encoding them independently, High-Resolution Large Vision-Language Models (HR-LVLMs) have demonstrated remarkable fine-grain…
Global Semantic-Guided Sub-image Feature Weight Allocation in High-Resolution Large Vision-Language Models
Yuxuan Liang, Xu Li, Xiaolei Chen +5
As the demand for high-resolution image processing in Large Vision-Language Models (LVLMs) grows, sub-image partitioning has become a popular approach for mitigating visual informa…
Instruction-Guided Fusion of Multi-Layer Visual Features in Large Vision-Language Models
Xu Li, Yi Zheng, Haotian Chen +5
Large Vision-Language Models (LVLMs) have achieved remarkable success in a wide range of multimodal tasks by integrating pre-trained vision encoders and large language models. Howe…
GAT-COBO: Cost-Sensitive Graph Neural Network for Telecom Fraud Detection
Xinxin Hu, Haotian Chen, Junjie Zhang +5
Along with the rapid evolution of mobile communication technologies, such as 5G, there has been a drastically increase in telecom fraud, which significantly dissipates individual f…
Cost Sensitive GNN-based Imbalanced Learning for Mobile Social Network Fraud Detection
Xinxin Hu, Haotian Chen, Hongchang Chen +5
With the rapid development of mobile networks, the people's social contacts have been considerably facilitated. However, the rise of mobile social network fraud upon those networks…