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Look Back to Move Forward: Learning to Revisit for Agentic Compositional Image Generation

L5 · ResearcherResearcharXiv· 10/12/2026

Introduces novel reinforcement learning techniques for improving multi-step image generation workflows.

AI Summary

Researchers propose GenRevisit, an agentic framework that enables AI image generators to revisit previous image states during iterative refinement for better compositional generation.

Excerpt

Text-to-image models have made remarkable progress in visual fidelity and instruction following, yet complex compositional generation remains challenging. Existing agentic approaches address this limitation through iterative generation and editing, adapting their actions based on interaction history. However, they typically fix the continuation state (i.e., the image from which refinement proceeds) to the latest image. Since iterative editing is not necessarily monotonic, the agent may continue

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