collaborators

14 papers

cs.CV2026

Vision as Unified Multimodal Generation

Xiaoyang Han, Jianhua Li, Kewang Deng +14

We formulate computer vision as unified multimodal generation, where heterogeneous visual tasks are expressed in the native text and image generation spaces of a unified multimodal…

cs.CV2026

From Pixels to Words -- Towards Native One-Vision Models at Scale

Haiwen Diao, Jiahao Wang, Penghao Wu +18

Current vision-language models (VLMs) typically stitch together separate image encoders and language decoders via multi-stage alignment, a modular framework that inevitably fragmen…

cs.CV2026

The Prism Hypothesis: Harmonizing Semantic and Pixel Representations via Unified Autoencoding

Weichen Fan, Haiwen Diao, Quan Wang +2

Deep representations across modalities are inherently intertwined. In this paper, we systematically analyze the spectral characteristics of various semantic and pixel encoders. Int…

cs.CV2026

Scaling Spatial Intelligence with Multimodal Foundation Models

Zhongang Cai, Ruisi Wang, Chenyang Gu +26

Despite remarkable progress, multimodal foundation models still exhibit surprising deficiencies in spatial intelligence. In this work, we explore scaling up multimodal foundation m…

cs.CV2026

ConsistCompose: Unified Multimodal Layout Control for Image Composition

Xuanke Shi, Boxuan Li, Xiaoyang Han +4

Unified multimodal models that couple visual understanding with image generation have advanced rapidly, yet most systems still focus on visual grounding-aligning language with imag…

cs.CV2025

Holistic Evaluation of Multimodal LLMs on Spatial Intelligence

Zhongang Cai, Yubo Wang, Qingping Sun +21

Multimodal models have achieved remarkable progress in recent years. Nevertheless, they continue to exhibit notable limitations in spatial understanding and reasoning, the very cap…