ImageEdit-R1: Boosting Multi-Agent Image Editing via Reinforcement Learning

• URL: http://arxiv.org/abs/2603.08059v1
• Date: Mon, 09 Mar 2026 07:50:14 GMT
• Title: ImageEdit-R1: Boosting Multi-Agent Image Editing via Reinforcement Learning
• Abstract summary: Image editing systems often struggle with complex, indirect, or multi-step user instructions.<n>We propose ImageEdit-R1, a multi-agent framework for intelligent image editing.<n>Our method treats image editing as a sequential decision-making problem, enabling dynamic and context-aware editing strategies.
• Score: 20.61925053714293
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: With the rapid advancement of commercial multi-modal models, image editing has garnered significant attention due to its widespread applicability in daily life. Despite impressive progress, existing image editing systems, particularly closed-source or proprietary models, often struggle with complex, indirect, or multi-step user instructions. These limitations hinder their ability to perform nuanced, context-aware edits that align with human intent. In this work, we propose ImageEdit-R1, a multi-agent framework for intelligent image editing that leverages reinforcement learning to coordinate high-level decision-making across a set of specialized, pretrained vision-language and generative agents. Each agent is responsible for distinct capabilities--such as understanding user intent, identifying regions of interest, selecting appropriate editing actions, and synthesizing visual content--while reinforcement learning governs their collaboration to ensure coherent and goal-directed behavior. Unlike existing approaches that rely on monolithic models or hand-crafted pipelines, our method treats image editing as a sequential decision-making problem, enabling dynamic and context-aware editing strategies. Experimental results demonstrate that ImageEdit-R1 consistently outperforms both individual closed-source diffusion models and alternative multi-agent framework baselines across multiple image editing datasets.

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