ProCUA SFT ProCUA SFT is a large scale synthetic trajectory dataset for training computer use agents (CUAs): models that operate graphical desktop environments from screenshots using mouse, keyboard, and code like actions. The dataset accompanies the ProCUA SFT Technical Report and is designed for supervised fine tuning of screenshot based desktop agents. This repository contains the raw trajectory artifacts used to construct those step prefix SFT samples: trajectory JSON files and their corresponding screenshots. To keep the Hugging Face repository reliable for a dataset with millions of small files, trajectories are distributed as compressed tar shards under shards/ . Dataset Summary ProCUA SFT was produced by an automated pipeline that uses a single VLM, Kimi K2.5, in multiple roles: goal generation, precondition verification, and trajectory rollout. The pipeline synthesizes grounded desktop tasks, verifies that task preconditions hold before rollout, executes the task in a full desktop environment, and records screenshot action trajectories. The dataset is grounded in realistic desktop content and configurations, including: multi application desktop configurations adapted from…
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