Generation-to-Understanding synergy lets multimodal models create self-generated visual edits as intermediate steps, improving performance on twelve benchmarks while revealing limits in task-aligned self-reflection.
Viescore: Towards explainable metrics for conditional image synthesis evaluation
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Reversing the Flow: Generation-to-Understanding Synergy in Large Multimodal Models
Generation-to-Understanding synergy lets multimodal models create self-generated visual edits as intermediate steps, improving performance on twelve benchmarks while revealing limits in task-aligned self-reflection.