{"ID":2837120,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.20614","arxiv_id":"2511.20614","title":"The Consistency Critic: Correcting Inconsistencies in Generated Images via Reference-Guided Attentive Alignment","abstract":"Previous works have explored various customized generation tasks given a reference image, but they still face limitations in generating consistent fine-grained details. In this paper, our aim is to solve the inconsistency problem of generated images by applying a reference-guided post-editing approach and present our ImageCritic. We first construct a dataset of reference-degraded-target triplets obtained via VLM-based selection and explicit degradation, which effectively simulates the common inaccuracies or inconsistencies observed in existing generation models. Furthermore, building on a thorough examination of the model's attention mechanisms and intrinsic representations, we accordingly devise an attention alignment loss and a detail encoder to precisely rectify inconsistencies. ImageCritic can be integrated into an agent framework to automatically detect inconsistencies and correct them with multi-round and local editing in complex scenarios. Extensive experiments demonstrate that ImageCritic can effectively resolve detail-related issues in various customized generation scenarios, providing significant improvements over existing methods.","short_abstract":"Previous works have explored various customized generation tasks given a reference image, but they still face limitations in generating consistent fine-grained details. In this paper, our aim is to solve the inconsistency problem of generated images by applying a reference-guided post-editing approach and present our I...","url_abs":"https://arxiv.org/abs/2511.20614","url_pdf":"https://arxiv.org/pdf/2511.20614v1","authors":"[\"Ziheng Ouyang\",\"Yiren Song\",\"Yaoli Liu\",\"Shihao Zhu\",\"Qibin Hou\",\"Ming-Ming Cheng\",\"Mike Zheng Shou\"]","published":"2025-11-25T18:40:25Z","proceeding":"cs.CV","tasks":"[\"cs.CV\"]","methods":"[]","has_code":false}