Uncovering Understanding-Generation Synergy in Native Unified Multimodal Models: From Representation, Task to System
The paper argues that unified multimodal models only gain real synergy when shared learning is paired with architectural specialization.
The authors test visual understanding and generation together in a native model without pretrained vision priors. They find each objective can help the other, but a single shared computation path lets one side dominate. A task-decoupled design preserves semantic interaction while separating conflicting visual computation. In their system-level test, an end-to-end unified model beats a matched planner-executor pipeline on tasks requiring both understanding and generation. HF Daily Papers' note
The authors test visual understanding and generation together in a native model without pretrained vision priors. They find each objective can help the other, but a single shared computation path lets one side dominate. A task-decoupled design preserves semantic interaction while separating conflicting visual computation. In their system-level test, an end-to-end unified model beats a matched planner-executor pipeline on tasks requiring both understanding and generation. HF Daily Papers' note
score 5