7 citations · 8 across the 7 of their papers we have counts for
8 papers
SlimVLM: Sensitivity-aware Dynamic Structured Pruning with Adaptive Visual Token Selection for Efficient Vision-Language Models
Yaozhi Wen, Jialong Guo, Zhenliang Ni +2
While Vision-Language Models (VLMs) have demonstrated remarkable performance in processing and understanding both text and images, their large parameter sizes lead to significant c…
VLM-Pruner: Buffering for Spatial Sparsity in an Efficient VLM Centrifugal Token Pruning Paradigm
Zhenkai Wu, Xiaowen Ma, Zhenliang Ni +4
Vision-language models (VLMs) excel at image understanding tasks, but the large number of visual tokens imposes significant computational costs, hindering deployment on mobile devi…
Ada-MoGE: Adaptive Mixture of Gaussian Expert Model for Time Series Forecasting
Zhenliang Ni, Xiaowen Ma, Zhenkai Wu +3
Multivariate time series forecasts are widely used, such as industrial, transportation and financial forecasts. However, the dominant frequencies in time series may shift with the…
Expert Merging: Model Merging with Unsupervised Expert Alignment and Importance-Guided Layer Chunking
Dengming Zhang, Xiaowen Ma, Zhenliang Ni +4
Model merging, which combines multiple domain-specialized experts into a single model, offers a practical path to endow Large Language Models (LLMs) and Multimodal Large Language M…
TimePro: Efficient Multivariate Long-term Time Series Forecasting with Variable- and Time-Aware Hyper-state
Xiaowen Ma, Zhenliang Ni, Shuai Xiao +1
In long-term time series forecasting, different variables often influence the target variable over distinct time intervals, a challenge known as the multi-delay issue. Traditional…
TinyViM: Frequency Decoupling for Tiny Hybrid Vision Mamba
Xiaowen Ma, Zhenliang Ni, Xinghao Chen
Mamba has shown great potential for computer vision due to its linear complexity in modeling the global context with respect to the input length. However, existing lightweight Mamb…
SSA-Seg: Semantic and Spatial Adaptive Pixel-level Classifier for Semantic Segmentation
Xiaowen Ma, Zhenliang Ni, Xinghao Chen
Vanilla pixel-level classifiers for semantic segmentation are based on a certain paradigm, involving the inner product of fixed prototypes obtained from the training set and pixel…
Context-Guided Spatial Feature Reconstruction for Efficient Semantic Segmentation
Zhenliang Ni, Xinghao Chen, Yingjie Zhai +2
Semantic segmentation is an important task for numerous applications but it is still quite challenging to achieve advanced performance with limited computational costs. In this pap…