| --- |
| license: apache-2.0 |
| task_categories: [image-text-to-text] |
| tags: [mobile-gui-agent, agent-memory, reinforcement-learning, conact] |
| --- |
| |
| # MemGUI-3K-Verl |
|
|
| RL prompt corpus of the ICLR 2027 submission *FARPO: Folding-Aware Reward-Decoupled Policy Optimization for Long-Horizon Mobile GUI Agents* (project MemGUI-RL; project page: |
| https://memgui-rl-anonymous.github.io/). Every record is one annotated state of a MemGUI-3K |
| trajectory in the ConAct conversation format consumed by the FARPO trainer |
| (https://github.com/memgui-rl-anonymous/MemGUI-RL): |
|
|
| | file | states | trajectories | use | |
| | --- | --- | --- | --- | |
| | `memgui3k_train_verl.json` | 73,807 | 2,661 | RL prompts (positive states only are used; folding-aware sampling controls the span:step ratio) | |
| | `memgui3k_test_verl.json` | 8,296 | 295 | held-out validation (never filtered; 5,941 positive states) | |
|
|
| Each record has `task_id`, `step_number`, `is_positive`, `bad_step`, `raw_response` (the annotated |
| ConAct response: `<thinking>`, `<folding>`, `<tool_call>`, `<ui_observation>`, `<action_intent>`), |
| `conversations` (system prompt, user prompt with the folded history / UI memory / recent step record |
| and the screenshot, reference assistant turn) and `metadata` (impact / reasonableness labels of the |
| step, trajectory ids). |
|
|
| Screenshots are **not** duplicated here: image references have the form |
| `MemGUI-3K/images/<task>_<attempt>_step_<k>.png` and resolve against the MemGUI-3K release |
| (https://huggingface.co/datasets/memgui-agent-anonymous/MemGUI-3K). Set `MEMGUI_IMAGE_ROOT` to the |
| directory that contains `MemGUI-3K/` when training. |
|
|
