32 citations · 46 across the 20 of their papers we have counts for
10 papers · 1 filter
LinMorph: Learning to Morph Weights for Efficient Video DiT Linearization
Lingyi Long, Congyue Zhao, Xiaoou Li +2
Post-hoc linearization is an attractive way to accelerate pretrained Video Diffusion Transformers (Video DiTs), yet existing methods largely treat the quality loss induced by atten…
Adversarial Error Correction for Visual Autoregressive Generation
Ligong Bi, Tao Huang, Jianyuan Guo +1
Visual Autoregressive (VAR) models have emerged as a powerful paradigm for image synthesis by performing hierarchical next-scale prediction. However, VAR models are inherently pron…
Efficient Conditional Generation on Scale-based Visual Autoregressive Models
Jiaqi Liu, Tao Huang, Chang Xu
Recent advances in autoregressive (AR) models have demonstrated their potential to rival diffusion models in image synthesis. However, for complex spatially-conditioned generation,…
Rethinking Causal Mask Attention for Vision-Language Inference
Xiaohuan Pei, Tao Huang, YanXiang Ma +1
Causal attention has become a foundational mechanism in autoregressive vision-language models (VLMs), unifying textual and visual inputs under a single generative framework. Howeve…
Learning Mask Invariant Mutual Information for Masked Image Modeling
Tao Huang, Yanxiang Ma, Shan You +1
Masked autoencoders (MAEs) represent a prominent self-supervised learning paradigm in computer vision. Despite their empirical success, the underlying mechanisms of MAEs remain ins…
Cross-Self KV Cache Pruning for Efficient Vision-Language Inference
Xiaohuan Pei, Tao Huang, Chang Xu
KV cache pruning has emerged as a promising technique for reducing memory and computation costs in long-context auto-regressive generation. Existing methods for vision-language mod…
Training-free Composite Scene Generation for Layout-to-Image Synthesis
Jiaqi Liu, Tao Huang, Chang Xu
Recent breakthroughs in text-to-image diffusion models have significantly advanced the generation of high-fidelity, photo-realistic images from textual descriptions. Yet, these mod…
EfficientVMamba: Atrous Selective Scan for Light Weight Visual Mamba
Xiaohuan Pei, Tao Huang, Chang Xu
Prior efforts in light-weight model development mainly centered on CNN and Transformer-based designs yet faced persistent challenges. CNNs adept at local feature extraction comprom…
LocalMamba: Visual State Space Model with Windowed Selective Scan
Tao Huang, Xiaohuan Pei, Shan You +3
Recent advancements in state space models, notably Mamba, have demonstrated significant progress in modeling long sequences for tasks like language understanding. Yet, their applic…
Active Generation for Image Classification
Tao Huang, Jiaqi Liu, Shan You +1
Recently, the growing capabilities of deep generative models have underscored their potential in enhancing image classification accuracy. However, existing methods often demand the…