3 papers
cs.CV2026
Cross-Resolution Diffusion Models via Network Pruning
Jiaxuan Ren, Junhan Zhu, Huan Wang
Diffusion models have demonstrated impressive image synthesis performance, yet many UNet-based models are trained at certain fixed resolutions. Their quality tends to degrade when…
cs.CV2026
LVOmniBench: Pioneering Long Audio-Video Understanding Evaluation for Omnimodal LLMs
Keda Tao, Yuhua Zheng, Jia Xu +13
Recent advancements in omnimodal large language models (OmniLLMs) have significantly improved the comprehension of audio and video inputs. However, current evaluations primarily fo…
cs.CV2026
OBS-Diff: Accurate Pruning For Diffusion Models in One-Shot
Junhan Zhu, Hesong Wang, Mingluo Su +2
Large-scale text-to-image diffusion models, while powerful, suffer from prohibitive computational cost. Existing one-shot network pruning methods can hardly be directly applied to…