When Does Visual Generation Help Visual Understanding in Unified Multimodal Models?
Unified multimodal models (UMMs) can perform both understanding and generation, raising a central question: can visual generation improve understanding? Existing evaluations provide mixed evidence, but confound task difficulty, reasoning paradigms, and the closed-loop interaction between generation and understanding. We introduce VGAU-Diag, a fine-grained evaluation framework for vision generation-assisted understanding. It stratifies samples by difficulty, enables unified evaluation of multiple reasoning paradigms, and uses Oracle-Assisted Reference Protocols. Our analysis shows that generated visual aids help on easier instances but become unreliable as reasoning complexity increases. O...
| Authors | Yubo Zhu, Zhehan Kan, Jingyi Yang et al. |
|---|---|
| Primary category | cs.CV |
| Published | 23 August 2026 |
| Last updated at source | 25 August 2026 |
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