9 papers
Fourier Compressor: Frequency-Domain Visual Token Compression for Vision-Language Models
Huanyu Wang, Jushi Kai, Haoli Bai +4
Vision-Language Models (VLMs) incur substantial computational overhead and inference latency due to the large number of vision tokens introduced by high-resolution image and video…
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…
Autoregressive Image Generation with Randomized Parallel Decoding
Haopeng Li, Jinyue Yang, Guoqi Li +1
We introduce ARPG, a novel visual Autoregressive model that enables Randomized Parallel Generation, addressing the inherent limitations of conventional raster-order approaches, whi…
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…
ERNIE 5.0 Technical Report
Haifeng Wang, Hua Wu, Tian Wu +432
In this report, we introduce ERNIE 5.0, a natively autoregressive foundation model desinged for unified multimodal understanding and generation across text, image, video, and audio…
FreeBlend: Advancing Concept Blending with Staged Feedback-Driven Interpolation Diffusion
Yufan Zhou, Haoyu Shen, Huan Wang
Concept blending is a promising yet underexplored area in generative models. While recent approaches, such as embedding mixing and latent modification based on structural sketches,…