3 papers
cs.CV2026
Collaborative Multi-Mode Pruning for Vision-Language Models
Zimeng Wu, Yunhong Wang, Donghao Wang +1
Vision-Language Models (VLMs) have advanced rapidly within the unified Transformer architecture, yet their deployment on resource-constrained devices remains challenging due to hig…
cs.CL2026
Probe and Skip: Self-Predictive Token Skipping for Efficient Long-Context LLM Inference
Zimeng Wu, Donghao Wang, Chaozhe Jin +2
Long-context inference enhances the reasoning capability of Large Language Models (LLMs), but incurs significant computational overhead. Token-oriented methods, such as pruning and…
cs.CV2024
TCAQ-DM: Timestep-Channel Adaptive Quantization for Diffusion Models
Haocheng Huang, Jiaxin Chen, Jinyang Guo +2
Diffusion models have achieved remarkable success in the image and video generation tasks. Nevertheless, they often require a large amount of memory and time overhead during infere…