Qi Zhang
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Qi Zhang
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Qi Zhang
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Qi Zhang
2025
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AXIS: Efficient Human-Agent-Computer Interaction with API-First LLM-Based Agents
Junting Lu
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Zhiyang Zhang
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Fangkai Yang
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Jue Zhang
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Lu Wang
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Chao Du
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Qingwei Lin
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Saravan Rajmohan
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Dongmei Zhang
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Qi Zhang
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Multimodal large language models (MLLMs) have enabled LLM-based agents to directly interact with application user interfaces (UIs), enhancing agents’ performance in complex tasks. However, these agents often suffer from high latency and low reliability due to the extensive sequential UI interactions. To address this issue, we propose AXIS, a novel LLM-based agents framework that prioritize actions through application programming interfaces (APIs) over UI actions. This framework also facilitates the creation and expansion of APIs through automated exploration of applications. Our experiments on Microsoft Word demonstrate that AXIS reduces task completion time by 65%-70% and cognitive workload by 38%-53%, while maintaining accuracy of 97%-98% compared to humans. Our work contributes to a new human-agent-computer interaction (HACI) framework and explores a fresh UI design principle for application providers to turn applications into agents in the era of LLMs, paving the way towards an agent-centric operating system (Agent OS). The code and dataset will be available at https://aka.ms/haci_axis.
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UFO: A UI-Focused Agent for Windows OS Interaction
Chaoyun Zhang
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Liqun Li
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Shilin He
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Xu Zhang
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Bo Qiao
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Si Qin
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Minghua Ma
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Yu Kang
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Qingwei Lin
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Saravan Rajmohan
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Dongmei Zhang
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Qi Zhang
Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
We introduce UFO, a UI-Fcused agent designed to fulfill user requests tailored to Windows OS applications by observing and analyzing the GUI and control information of these applications. UFO utilizes a hierarchical dual-agent framework that decomposes user requests using a divide-and-conquer approach, enabling seamless navigation and addressing sub-tasks across multiple applications. It also incorporates a control interaction module tailored for Windows OS, which detects control elements effectively and allows for fully automated execution. As a result, UFO simplifies complex and time-consuming processes into tasks that can be completed with natural language commands.We conducted testing of UFO across 9 popular Windows applications, encompassing a variety of scenarios. The results derived from both quantitative metrics and real-case studies, underscore the superior effectiveness of UFOin fulfilling user requests. To the best of our knowledge, UFO stands as the first UI agent specifically tailored for task completion within the Windows OS.