arXiv:2601. 18305v2 Announce Type: replace Abstract: Despite numerous Graphical User Interface (GUI) agents claiming to automate user interaction tasks, to date, few achieve satisfactory interaction capability with human users in real-world scenarios.
arXiv:2607. 13027v1 Announce Type: cross Abstract: Large Language Model (LLM) agents have moved beyond generating responses to executing multi-step tasks by calling tools, observing the results, and iteratively deciding the next action.
arXiv:2606. 06322v1 Announce Type: new Abstract: GUI agents - vision-based models that control desktops, web browsers, and mobile devices through graphical user interfaces - promise to automate a wide range of digital tasks.
arXiv:2606. 31410v1 Announce Type: new Abstract: Graphical user interface (GUI) agents build on vision-language models to complete user tasks end-to-end in real applications through interface actions such as tapping, swiping, text entry, and navigation.
arXiv:2607. 04425v2 Announce Type: replace-cross Abstract: Recent advances in multimodal foundation models and agent systems have driven GUI agents from single-platform task execution toward cross-platform interaction.
arXiv:2511. 07332v2 Announce Type: replace-cross Abstract: Building reliable computer-use agents requires grounding: accurately connecting natural language instructions to the correct on-screen elements.
arXiv:2607. 22689v1 Announce Type: new Abstract: Graphical user interface (GUI) agents are systems powered by large multimodal models (LMMs).
The paper introduces a hybrid interaction model for mobile GUI agents that combines app-native deeplinks with traditional GUI actions. By statically analyzing apps to discover candidate deeplinks, validating them on real devices, and cataloguing their landing screens, the authors create a verified deeplink catalog. Using this catalog, they develop GUI‑Hopper, which demonstrates improved task success rates in commercial applications through the use of deeplinks for direct navigation and GUI actions for other on‑screen operations.
arXiv:2608. 15930v1 Announce Type: new Abstract: Foundation GUI agents can automate complex digital tasks, but deployment is hindered by scarce and biased training data, ambiguous prompts, and unreliable execution.
AgentLens is a mobile GUI agent that adapts its visual communication during task execution, offering Full UI, Partial UI, and GenUI modalities. It uses a Virtual Display to allow background operation while selectively overlaying visual information. In a study with 21 participants, 85.7% preferred AgentLens, which also scored highest on usability and adoption intent.
arXiv:2606. 03103v1 Announce Type: new Abstract: Real-world professional desktop workflows in specialized creative and engineering software unfold over long horizons and often require human-in-the-loop coordination, where agents proactively seek necessary information and users provide additional instructions, clarifications, feedback, or corrections as the task progresses.
arXiv:2609.22000v1 Announce Type: new Abstract: Computer-use agents (CUAs) have advanced along two separate lines: graphical interaction and software development through code and the command line. Re...
Computer use agents (CUAs) have demonstrated strong capabilities in completing digital tasks. However, existing CUAs either rely solely on graphical user interface (GUI) interactions, which are often...