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cs.CV2026

ChatUMM: Robust Context Tracking for Conversational Interleaved Generation

Wenxun Dai, Zhiyuan Zhao, Yule Zhong +12

Unified multimodal models (UMMs) have achieved remarkable progress yet remain constrained by a single-turn interaction paradigm, effectively functioning as solvers for independent…

cs.CV2026

Refinement via Regeneration: Enlarging Modification Space Boosts Image Refinement in Unified Multimodal Models

Jiayi Guo, Linqing Wang, Jiangshan Wang +6

Unified multimodal models (UMMs) integrate visual understanding and generation within a single framework. For text-to-image (T2I) tasks, this unified capability allows UMMs to refi…

cs.CV2026

Meta-CoT: Enhancing Granularity and Generalization in Image Editing

Shiyi Zhang, Yiji Cheng, Tiankai Hang +8

Unified multi-modal understanding/generative models have shown improved image editing performance by incorporating fine-grained understanding into their Chain-of-Thought (CoT) proc…

cs.CV2026

Pref-GRPO: Pairwise Preference Reward-based GRPO for Stable Text-to-Image Reinforcement Learning

Yibin Wang, Zhimin Li, Yuhang Zang +6

Recent advancements highlight the importance of GRPO-based reinforcement learning methods and benchmarking in enhancing text-to-image (T2I) generation. However, current methods usi…

cs.CV2026

TAG-MoE: Task-Aware Gating for Unified Generative Mixture-of-Experts

Yu Xu, Hongbin Yan, Juan Cao +11

Unified image generation and editing models suffer from severe task interference in dense diffusion transformers architectures, where a shared parameter space must compromise betwe…

cs.CV2026

Generative Visual Chain-of-Thought for Image Editing

Zijin Yin, Tiankai Hang, Yiji Cheng +9

Existing image editing methods struggle to perceive where to edit, especially under complex scenes and nuanced spatial instructions. To address this issue, we propose Generative Vi…