[2603.28618] Seeing with You: Perception-Reasoning Coevolution for Multimodal Reasoning

Computer Science > Artificial Intelligence arXiv:2603.28618 (cs) [Submitted on 30 Mar 2026] Title:Seeing with You: Perception-Reasoning Coevolution for Multimodal Reasoning Authors:Ziqi Miao, Haonan Jia, Lijun Li, Chen Qian, Yuan Xiong, Wenting Yan, Jing Shao View a PDF of the paper titled Seeing with You: Perception-Reasoning Coevolution for Multimodal Reasoning, by Ziqi Miao and 6 other authors View PDF HTML (experimental) Abstract:Reinforcement learning with verifiable rewards (RLVR) has substantially enhanced the reasoning capabilities of multimodal large language models (MLLMs). However, existing RLVR approaches typically rely on outcome-driven optimization that updates both perception and reasoning using a shared reward based solely on the final answer. This shared reward blurs credit assignment, frequently improving reasoning patterns while failing to reliably enhance the accuracy of upstream visual evidence extraction. To address this perception bottleneck, we introduce PRCO (Perception-Reasoning Coevolution), a dual-role RLVR framework with a shared policy. PRCO consists of two cooperative roles: an Observer that generates an evidence caption tailored to the question and a Solver that predicts the final answer based on this caption. Crucially, PRCO employs role-specific reward signals: the Solver is optimized using verifiable outcome rewards on the final answer, while the Observer receives a utility reward derived from the Solver's downstream success. Extensive ex...