Source-reviewed research and assets tagged with Survey.
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Surveys multimodal memory using representation and management axes, distinguishing fixed-policy updates from policy evolution and comparing GUI memory evaluation with other modalities.
Surveys GUI-agent efficiency beyond task success: observation, context and memory, action, and planner or runtime cost.
Surveys modular agentic skill architectures, skill lifecycles, and security risks in autonomous tool- and interface-using agents.
Organizes security risks and defenses for persistent agent memory into six lifecycle phases and proposes five verifiable governance primitives.
This survey organizes agent skills by architecture, acquisition, deployment and security, including their role in computer-use systems and GUI grounding. It also proposes a permission and lifecycle governance framework for skill deployment.
Surveys agents that operate computers and phones through operating-system interfaces, covering components, capabilities, foundation models, frameworks, and benchmarks.
Systematizes safety and security threats to computer-using agents, with taxonomies of threats and defensive strategies.
Formalizes GUI tasks as Markov decision processes and traces agent training from prompting through supervised fine-tuning to reinforcement learning.
Reviews LLM-driven phone GUI agents with a taxonomy of agent frameworks, prompt- and training-based modeling, datasets, and benchmarks.
Frames GUI-agent trustworthiness as an execution gap and reviews failures, attacks, and defenses across perception, reasoning, and interaction.
Surveys foundation-model web agents through their architectures, training methods and trustworthiness. It organizes research on completing browser tasks from user instructions and identifies directions for further development.
Analyzes LLM-based GUI agents through four components (perception, exploration, planning, and interaction) and the methods used to evaluate them.
Compares API-driven and GUI-driven agents across architecture, development, and interaction considerations, discussing when hybrid approaches are useful.
Reviews 87 computer-use agents and 33 datasets through a taxonomy of operating domain, observation and action modalities, and agent design.
Categorizes GUI-agent benchmarks, evaluation metrics, architectures, and training methods, and proposes a unified perception, reasoning, planning, and acting framework.
Survey of LLM-brained GUI agents that carry out natural-language instructions across web, mobile, and desktop interfaces, organizing research and industry progress.
Surveys virtual agents for browsers, applications and operating systems, organizing prior work by task type, observation and action spaces, model strategies and evaluation methods. It examines screen-based interaction and keyboard, mouse and touch control, alongside transferability and long-sequence decision-making challenges.
Survey of (M)LLM-based GUI agents organized around their datasets and benchmarks, a unified agent framework with a taxonomy, and commercial applications.
Surveys multimodal mobile agents, organizing prompt-based and training-based approaches alongside evaluation benchmarks, supporting technologies, and open challenges in mobile task execution.
Presents a conceptual perception–reasoning–action framework and 12 potential attack scenarios for language agents, including hypothetical web-navigation attacks.
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