[2509.24897] RealUnify: Do Unified Models Truly Benefit from Unification? A Comprehensive Benchmark

Computer Science > Artificial Intelligence arXiv:2509.24897 (cs) [Submitted on 29 Sep 2025 (v1), last revised 20 Mar 2026 (this version, v2)] Title:RealUnify: Do Unified Models Truly Benefit from Unification? A Comprehensive Benchmark Authors:Yang Shi, Yuhao Dong, Yue Ding, Yuran Wang, Xuanyu Zhu, Sheng Zhou, Wenting Liu, Haochen Tian, Rundong Wang, Huanqian Wang, Zuyan Liu, Bohan Zeng, Ruizhe Chen, Qixun Wang, Zhuoran Zhang, Xinlong Chen, Chengzhuo Tong, Bozhou Li, Qiang Liu, Haotian Wang, Wenjing Yang, Yuanxing Zhang, Pengfei Wan, Yi-Fan Zhang, Ziwei Liu View a PDF of the paper titled RealUnify: Do Unified Models Truly Benefit from Unification? A Comprehensive Benchmark, by Yang Shi and 24 other authors View PDF HTML (experimental) Abstract:The integration of visual understanding and generation into unified multimodal models represents a significant stride toward general-purpose AI. However, a fundamental question remains unanswered by existing benchmarks: does this architectural unification actually enable synergetic interaction between the constituent capabilities? Existing evaluation paradigms, which primarily assess understanding and generation in isolation, are insufficient for determining whether a unified model can leverage its understanding to enhance its generation, or use generative simulation to facilitate deeper comprehension. To address this critical gap, we introduce RealUnify, a benchmark specifically designed to evaluate bidirectional capability synergy. ...