Datasets:
File size: 1,605 Bytes
d40bec0 a7b7b02 d40bec0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | ---
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.
|