OS-Symphony: A Holistic Framework for Robust and Generalist Computer-Using Agent

ybw, Jin Kaiming, Zhenyu Wu, Zhaoyang Liu, Qiushi, Zehao Li, JingJing Xie, Zhoumianze Liu, Fangzhi Xu, Kanzhi Cheng, Qingyun Li, Yian Wang, Yu Qiao, wz22, Zichen Ding

OS-Symphony: A Holistic Framework for Robust and Generalist Computer-Using Agent: 10 upvotes on Hugging Face Daily Papers, #8 of 42 papers on 2026-01-13. Day-by-day upvote history. It lost 18 votes when the Hub removed votes in bulk.

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.

Paper page on Hugging Face · arXiv

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