Understanding vs. Generation: Navigating Optimization Dilemma in Multimodal Models
Current research in multimodal models faces a key challenge where enhancing generative capabilities often comes at the expense of understanding, and vice versa. We analyzed this trade-off and identify the primary cause might be the potential conflict between generation and understanding, which creates a competitive dynamic within the model. To address this, we propose the Reason-Reflect-Refine (R3) framework. This innovative algorithm re-frames the single-step generation task into a multi-step process of "generate-understand-regenerate". By explicitly leveraging the model's understanding capability during generation, we successfully mitigate the optimization dilemma, achieved stronger generation results and improved understanding ability which are related to the generation process. This offers valuable insights for designing next-generation unified multimodal models. Code is available at https://github.com/sen-ye/R3.
69953f568d17d1ee8c10ecbc
Sen Ye
admin_assigned
2026-02-18T13:40:22.765Z
674736347f64a8dbfbf73f97
/avatars/35d825248230fe66c4ae88f153b7128e.svg
Sen Ye
sen-ye
user
sen-ye
69953f568d17d1ee8c10ecbd
Mengde Xu
admin_assigned
2026-02-18T13:40:30.096Z
63f5993afcf95ecac2b419b5
/avatars/a8c020080a84d9a663789c4fb19270e9.svg
Mengde Xu
Mendel192
user
Mendel192
69953f568d17d1ee8c10ecbe
Shuyang Gu
69953f568d17d1ee8c10ecbf
Di He
69953f568d17d1ee8c10ecc0
Liwei Wang
69953f568d17d1ee8c10ecc1
Han Hu
Understanding vs. Generation: Navigating Optimization Dilemma in Multimodal Models
Current research in multimodal models faces a key challenge where enhancing generative capabilities often comes at the expense of understanding, and vice versa. We analyzed this trade-off and identify the primary cause might be the potential conflict between generation and understanding, which creates a competitive dynamic within the model. To address this, we propose the Reason-Reflect-Refine (R3) framework. This innovative algorithm re-frames the single-step generation task into a multi-step process of "generate-understand-regenerate". By explicitly leveraging the model's understanding capability during generation, we successfully mitigate the optimization dilemma, achieved stronger generation results and improved understanding ability which are related to the generation process. This offers valuable insights for designing next-generation unified multimodal models. Code is available at https://github.com/sen-ye/R3.
The Reason-Reflect-Refine framework addresses the trade-off between generation and understanding in multimodal models by reformulating single-step generation into a multi-step process that explicitly incorporates understanding during generation.
multimodal models generative capabilities understanding capabilities optimization dilemma Reason-Reflect-Refine framework generate-understand-regenerate process