OS-Symphony: A Holistic Framework for Robust and Generalist Computer-Using Agent
Authors: name: Bowen Yang, name: Kaiming Jin, name: Zhenyu Wu, name: Zhaoyang Liu, name: Qiushi Sun, name: Zehao Li, name: JingJing Xie, name: Zhoumianze Liu, name: Fangzhi Xu, name: Kanzhi Cheng, name: Qingyun Li, name: Yian Wang, name: Yu Qiao, name: Zun Wang, name: Zichen Ding
Organization: university of science and technology  of china

While Vision-Language Models (VLMs) have significantly advanced Computer-Using Agents (CUAs), current frameworks struggle with robustness in long-horizon workflows and generalization in novel domains. These limitations stem from a lack of granular control over historical visual context curation and the absence of visual-aware tutorial retrieval. To bridge these gaps, we introduce OS-Symphony, a holistic framework that comprises an Orchestrator coordinating two key innovations for robust automation: (1) a Reflection-Memory Agent that utilizes milestone-driven long-term memory to enable trajectory-level self-correction, effectively mitigating visual context loss in long-horizon tasks; (2) Versatile Tool Agents featuring a Multimodal Searcher that adopts a SeeAct paradigm to navigate a browser-based sandbox to synthesize live, visually aligned tutorials, thereby resolving fidelity issues in unseen scenarios. Experimental results demonstrate that OS-Symphony delivers substantial performance gains across varying model scales, establishing new state-of-the-art results on three online benchmarks, notably achieving 65.84% on OSWorld.