Cradle
Framework in which foundation models control games and software from screenshots alone, acting through keyboard and mouse, shown on RDR2, Stardew Valley, Cities: Skylines and Dealer's Life 2.
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Framework in which foundation models control games and software from screenshots alone, acting through keyboard and mouse, shown on RDR2, Stardew Valley, Cities: Skylines and Dealer's Life 2.
Offline prompting and evaluation code for Dynamic Planning of Thoughts on Android-in-the-Wild, including action extraction and comparison with reference actions.
Released data-synthesis and evaluation scripts that distill planning and causal GUI knowledge into text for mid-training mobile interface agents.
A desktop trajectory-generation framework that moves from stochastic GUI exploration to inferred goals and multi-stage task completion, with retrospective reasoning annotations.
Query-inference training tools connecting screenshot grounding with GUI action reasoning, including preprocessing, query refinement and offline single-step evaluation on AndroidControl and AITZ.
Modular web-agent framework with browser control, planning, workflow memory, and tree-search components, plus web and extension interfaces.
An Android agent that combines global task planning and memory with a local action executor, using reflection to revise mobile interaction steps.
Android automation component with hierarchical planning, reflection and persistent tips/shortcuts learned across task sequences.
An Android client and Python-server agent that learns reusable app subtasks through exploration, selection, derivation and memory recall.
A framework that combines screenshots and accessibility state with agent tools for mobile-device tasks through command-line and Python interfaces.
Open-source library for generalist agents acting on an operating system's web, terminals, files and third-party apps, with the FRIDAY assistant, which takes custom tools and self-learns Excel tasks.
Human-cognition-transfer framework for PC agents: PC Tracker logs human computer use, cognition completion turns logs into cognitive trajectories, and a planner works with a grounding agent.
Multi-agent desktop automation component for Windows and macOS, combining active perception, task decomposition and reflection for workflows spanning applications.
A web-agent framework that separates high-level planning from action execution, with replanning and synthetic planner-data generation components.
A MiniWoB++ agent that uses explicit and implicit recursive criticism-and-improvement prompts to refine action plans and ground actions to browser state.
Environment and agent in which a vision-language model controls real desktops over VNC with mouse and keyboard in plan, act and reflect stages, plus a hand-annotated dataset of daily computer tasks.
A conversational web-agent implementation with candidate ranking and memory-assisted action planning, including optional memory simplification, refinement and self-reflection modules.
State-tracking prompts and experiment runners for language agents, including a WebShop implementation alongside text-based environments.
A computer-control research implementation that retrieves example trajectories from memory, abstracts task-relevant state and prompts an agent to navigate browser tasks.
An Android automation implementation that translates screenshot-based UI understanding into language descriptions for step-by-step LLM planning and action execution.
World-model and planning components that simulate web-action outcomes, with linked training data and model checkpoints.
Web-task reward functions, WorkArena data processing and GRPO training configurations for reasoning-oriented language agents.
Browser-agent course with worked lessons on structured web extraction and multi-step browser interaction, followed by AgentQ search and self-correction concepts.
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