activity
20242026
collaborators

11 papers

cs.AI2026

Branch-JEPA: Finite-Support Predictive Distributions for JEPA World Models

Zhi Song, Ximing Xing, Zhenchao Tang +9

Joint-embedding predictive architectures (JEPAs) learn dynamics by predicting future observations in representation space. Yet most JEPA world models return one latent successor, e…

cs.CV2026

SVGDreamer: Text Guided SVG Generation with Diffusion Model

Ximing Xing, Haitao Zhou, Chuang Wang +3

Text-guided scalable vector graphics (SVG) synthesis has broad applications in icon and sketch generation. However, existing text-to-SVG methods often suffer from limited editabili…

cs.LG2026

Hierarchical SVG Tokenization: Learning Compact Visual Programs for Scalable Vector Graphics Modeling

Ximing Xing, Ziteng Xue, Zhenxi Li +8

Recent large language models have shifted SVG generation from differentiable rendering optimization to autoregressive program synthesis. However, existing approaches still rely on…

cs.CV2026

Reason-SVG: Enhancing Structured Reasoning for Vector Graphics Generation with Reinforcement Learning

Ximing Xing, Ziteng Xue, Yandong Guan +3

Generating high-quality Scalable Vector Graphics (SVGs) is challenging for Large Language Models (LLMs), as it requires advanced reasoning for structural validity, semantic accurac…

cs.CV2026

SVGFusion: A VAE-Diffusion Transformer for Vector Graphic Generation

Ximing Xing, Juncheng Hu, Ziteng Xue +5

Generating high-quality Scalable Vector Graphics (SVGs) from text remains a significant challenge. Existing LLM-based models that generate SVG code as a flat token sequence struggl…

cs.CV2026

DiffSketcher: Text Guided Vector Sketch Synthesis through Latent Diffusion Models

Ximing Xing, Chuang Wang, Haitao Zhou +3

We demonstrate that pre-trained text-to-image diffusion models, despite being trained on raster images, possess a remarkable capacity to guide vector sketch synthesis. In this pape…