UniReason 1.0: A Unified Reasoning Framework for World Knowledge Aligned Image Generation and Editing

• URL: http://arxiv.org/abs/2602.02437v3
• Date: Sat, 07 Feb 2026 16:35:02 GMT
• Title: UniReason 1.0: A Unified Reasoning Framework for World Knowledge Aligned Image Generation and Editing
• Authors: Dianyi Wang, Chaofan Ma, Feng Han, Size Wu, Wei Song, Yibin Wang, Zhixiong Zhang, Tianhang Wang, Siyuan Wang, Zhongyu Wei, Jiaqi Wang,
• Abstract summary: multimodal models often struggle with complex synthesis tasks that demand deep reasoning.<n>We propose UniReason, a unified framework that harmonizes text-to-image generation and image editing.<n>We support this framework by systematically constructing a large-scale reasoning-centric dataset.
• Score: 44.071171929398076
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Unified multimodal models often struggle with complex synthesis tasks that demand deep reasoning, and typically treat text-to-image generation and image editing as isolated capabilities rather than interconnected reasoning steps. To address this, we propose UniReason, a unified framework that harmonizes these two tasks through two complementary reasoning paradigms. We incorporate world knowledge-enhanced textual reasoning into generation to infer implicit knowledge, and leverage editing capabilities for fine-grained editing-like visual refinement to further correct visual errors via self-reflection. This approach unifies generation and editing within a shared architecture, mirroring the human cognitive process of planning followed by refinement. We support this framework by systematically constructing a large-scale reasoning-centric dataset (~300k samples) covering five major knowledge domains (e.g., cultural commonsense, physics, etc.) for textual reasoning, alongside an agent-generated corpus for visual refinement. Extensive experiments demonstrate that UniReason achieves advanced performance on reasoning-intensive benchmarks such as WISE, KrisBench and UniREditBench, while maintaining superior general synthesis capabilities.

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