DocOS: Towards Proactive Document-Guided Actions in GUI Agents
The paper introduces DocOS, a benchmark aimed at enhancing the capabilities of GUI agents through proactive document-guided actions. This approach allows agents to autonomously search for relevant documentation to solve complex tasks. The study highlights the challenges agents face in locating information and executing precise actions based on retrieved instructions.
- ▪DocOS is designed to assess document-guided problem solving in interactive environments.
- ▪The proposed method enables GUI agents to search for documentation to resolve long-tailed tasks.
- ▪Experiments reveal that agents struggle with locating relevant information and grounding instructions into actions.
Opening excerpt (first ~120 words) tap to expand
Computer Science > Artificial Intelligence arXiv:2605.18048 (cs) [Submitted on 18 May 2026] Title:DocOS: Towards Proactive Document-Guided Actions in GUI Agents Authors:Jingjing Liu, Ziye Huang, Zihao Cheng, Zeming Liu, Jiahong Wu, Yuhang Guo, Kehai Chen, Yunhong Wang, Haifeng Wang View a PDF of the paper titled DocOS: Towards Proactive Document-Guided Actions in GUI Agents, by Jingjing Liu and 8 other authors View PDF HTML (experimental) Abstract:While Graphical User Interface (GUI) agents have shown promising performance in automated device interaction, they primarily depend on static parametric knowledge from pre-training or instruction tuning.
…
Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv cs.AI.
Discussion
0 commentsMore from arXiv cs.AI
