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cs.CV2026

WorldCast: Exploring Intelligent Visual Generation in World State Prediction

Wenhao Yan, Haodong Li, Xiaotong Li +9

Humans interpret multimodal observations of the world and forecast how it will evolve. Recent multimodal generative systems have demonstrated similar capabilities: they can integra…

cs.CV2025

OpenSubject: Leveraging Video-Derived Identity and Diversity Priors for Subject-driven Image Generation and Manipulation

Yexin Liu, Manyuan Zhang, Yueze Wang +8

Despite the promising progress in subject-driven image generation, current models often deviate from the reference identities and struggle in complex scenes with multiple subjects.…

cs.CV2025

EditThinker: Unlocking Iterative Reasoning for Any Image Editor

Hongyu Li, Manyuan Zhang, Dian Zheng +11

Instruction-based image editing has emerged as a prominent research area, which, benefiting from image generation foundation models, have achieved high aesthetic quality, making in…

cs.CV2025

OneThinker: All-in-one Reasoning Model for Image and Video

Kaituo Feng, Manyuan Zhang, Hongyu Li +11

Reinforcement learning (RL) has recently achieved remarkable success in eliciting visual reasoning within Multimodal Large Language Models (MLLMs). However, existing approaches typ…

cs.CV2025

AIA: Rethinking Architecture Decoupling Strategy In Unified Multimodal Model

Dian Zheng, Manyuan Zhang, Hongyu Li +7

Unified multimodal models for image generation and understanding represent a significant step toward AGI and have attracted widespread attention from researchers. The main challeng…

cs.CV2025

Counteracting Matthew Effect in Self-Improvement of LVLMs through Head-Tail Re-balancing

Xin Guo, Zhiheng Xi, Yiwen Ding +6

Self-improvement has emerged as a mainstream paradigm for advancing the reasoning capabilities of large vision-language models (LVLMs), where models explore and learn from successf…

cs.CV2025

CodePlot-CoT: Mathematical Visual Reasoning by Thinking with Code-Driven Images

Chengqi Duan, Kaiyue Sun, Rongyao Fang +10

Recent advances in Large Language Models (LLMs) and Vision Language Models (VLMs) have shown significant progress in mathematical reasoning, yet they still face a critical bottlene…

cs.CV2025

Think with 3D: Geometric Imagination Grounded Spatial Reasoning from Limited Views

Zhangquan Chen, Manyuan Zhang, Xinlei Yu +8

Though recent advances in vision-language models (VLMs) have achieved remarkable progress across a wide range of multimodal tasks, understanding 3D spatial relationships from limit…

cs.CV2025

MoTE: Mixture of Ternary Experts for Memory-efficient Large Multimodal Models

Hongyu Wang, Jiayu Xu, Ruiping Wang +5

Large multimodal Mixture-of-Experts (MoEs) effectively scale the model size to boost performance while maintaining fixed active parameters. However, previous works primarily utiliz…