[2603.03714] Order Is Not Layout: Order-to-Space Bias in Image Generation

Computer Science > Computation and Language arXiv:2603.03714 (cs) [Submitted on 4 Mar 2026] Title:Order Is Not Layout: Order-to-Space Bias in Image Generation Authors:Yongkang Zhang, Zonglin Zhao, Yuechen Zhang, Fei Ding, Pei Li, Wenxuan Wang View a PDF of the paper titled Order Is Not Layout: Order-to-Space Bias in Image Generation, by Yongkang Zhang and 5 other authors View PDF HTML (experimental) Abstract:We study a systematic bias in modern image generation models: the mention order of entities in text spuriously determines spatial layout and entity--role binding. We term this phenomenon Order-to-Space Bias (OTS) and show that it arises in both text-to-image and image-to-image generation, often overriding grounded cues and causing incorrect layouts or swapped assignments. To quantify OTS, we introduce OTS-Bench, which isolates order effects with paired prompts differing only in entity order and evaluates models along two dimensions: homogenization and correctness. Experiments show that Order-to-Space Bias (OTS) is widespread in modern image generation models, and provide evidence that it is primarily data-driven and manifests during the early stages of layout formation. Motivated by this insight, we show that both targeted fine-tuning and early-stage intervention strategies can substantially reduce OTS, while preserving generation quality. Subjects: Computation and Language (cs.CL); Artificial Intelligence (cs.AI); Computer Vision and Pattern Recognition (cs.CV); Multi...