Simplify README

README.md

@@ -20,82 +20,24 @@ configs:
 
 # GroundGUI_RL
 
-A 12,600-prompt reinforcement-learning corpus for desktop GUI grounding. Each
-prompt is a screenshot plus a natural-language instruction, and the reward is
-whether the predicted click falls inside the target element's bounding box.
+A reinforcement-learning (RLOO) corpus for desktop GUI grounding: 12,600
+prompts over 11,205 screenshots from 87 desktop applications. Each prompt is a
+screenshot plus a natural-language instruction, and the reward is whether the
+predicted click lands inside the target element's bounding box.
 
-**All content comes from [GroundCUA](https://huggingface.co/datasets/ServiceNow/GroundCUA)**
-(MIT). The screenshots are byte-identical to GroundCUA's, and the instructions
-and boxes are GroundCUA's annotations. This release adds only sample
-selection, slice mixing and formatting into a Qwen3-VL `computer_use`
-tool-call prompt. Please cite GroundCUA (below) if you use it.
-
-| | |
-|---|---|
-| Prompts | 12,600 |
-| Screenshots | 11,205 (at most 2 prompts per image) |
-| Applications | 87 desktop apps (from GroundCUA) |
-| Size | ~4.9 GB (10 parquet shards, images embedded) |
-
-## Layout
-
-```
-GroundGUI_RL/
-├── data/train-0000{0..9}-of-00010.parquet   # 12,600 rows, screenshots embedded as image bytes
-├── SHA256SUMS
-├── LICENSE
-└── README.md
-```
-
-## Record format
-
-```text
-{
-  "images": [<PIL.Image 1920x1008>],
-  "messages": [
-    {"role": "system",    "content": "<computer_use tool definition; screen given as 1000x1000>"},
-    {"role": "user",      "content": "<image>\nSelect a gradient to apply a smooth color transition ..."},
-    {"role": "assistant", "content": "<tool_call>\n{\"name\": \"computer_use\", \"arguments\": {\"action\": \"left_click\", \"coordinate\": [96, 399]}}\n</tool_call>"}
-  ],
-  "solution": {"name": "mobile_use", "arguments": {"action": "click", "coordinate": [139, 381, 232, 426]}},
-  "additional_paras": "{\"image_size\": [1920, 1008], \"app\": \"Krita\", \"ui_type\": \"icon\", ...}",
-  "sample_id": 4026033
-}
-```
-
-Coordinate conventions (note that the two fields use different units):
-
-- `solution.arguments.coordinate` is the target box `[x1, y1, x2, y2]` in
-  **absolute pixels** of the original image. Reward functions should
-  normalise it with `image_size`.
-- The assistant turn is a reference answer: the box centre in **0–1000
-  normalised** coordinates (Qwen3-VL convention). It is useful for SFT
-  warm-up. An RL reward should use `solution`.
-- `additional_paras` is a **JSON string**, not an object.
-
-`additional_paras` fields:
-
-| field | meaning |
-|---|---|
-| `image_size` | `[width, height]` in pixels (matches the PNG header for every row) |
-| `app` | GroundCUA application name |
-| `ui_type` | `icon` or `text` element |
-| `register` | `functional_instruction`, `spatial_relation` or `bare_label` |
-| `source` | which GroundCUA annotation file the instruction came from |
-| `elem_text` | GroundCUA element text of the target |
-| `area_frac` | target box area / image area |
-| `slice` | mixing slice (below) |
-
-## Slices
+All screenshots, instructions and boxes come from
+[GroundCUA](https://huggingface.co/datasets/ServiceNow/GroundCUA) (MIT). This
+release only selects and mixes samples and formats them as Qwen3-VL
+`computer_use` tool-call prompts.
 
 | slice | rows | content |
 |---|---:|---|
-| `base_icon_func` | 4,848 | GroundCUA functional instructions targeting icon elements |
-| `base_text_func` | 1,500 | GroundCUA functional instructions targeting text elements |
-| `icon_func_new` | 1,652 | additional functional instructions on icon elements |
-| `bare_label` | 2,000 | the element's own label as the instruction, e.g. "Wrap Text." (mostly text-labelled buttons) |
-| `spatial` | 2,000 | GroundCUA spatial-relation instructions, e.g. "... immediately right of \"app icon\"" (about 79% horizontal) |
-| `small` | 600 | small targets, 80–250 ppm of the image area |
+| `base_icon_func` | 4,848 | functional instructions, icon targets |
+| `base_text_func` | 1,500 | functional instructions, text targets |
+| `icon_func_new` | 1,652 | more functional instructions, icon targets |
+| `bare_label` | 2,000 | the element's label as the instruction, e.g. "Wrap Text." |
+| `spatial` | 2,000 | spatial relations, e.g. "... immediately right of \"app icon\"" |
+| `small` | 600 | small targets (80–250 ppm of the image area) |
 
 ## Usage
 
@@ -105,21 +47,20 @@ from datasets import load_dataset
 
 ds = load_dataset("tjcaspar/GroundGUI_RL", split="train")
 row = ds[0]
-img = row["images"][0]                         # PIL.Image
-extra = json.loads(row["additional_paras"])    # image_size, slice, ...
-x1, y1, x2, y2 = row["solution"]["arguments"]["coordinate"]   # pixels
+img = row["images"][0]                                       # PIL.Image
+x1, y1, x2, y2 = row["solution"]["arguments"]["coordinate"]  # target box, absolute pixels
+extra = json.loads(row["additional_paras"])                  # JSON string: image_size, app, slice, ...
 ```
 
-ms-swift (GRPO / RLOO) can take the hub id directly:
-
-```bash
-swift rlhf --rlhf_type grpo --dataset tjcaspar/GroundGUI_RL --reward_funcs <your-bbox-hit-reward> ...
-```
+`messages` holds the system, user and assistant turns. The assistant turn is
+a reference answer: the box centre in 0–1000 normalised coordinates. Compute
+the reward from `solution`.
 
-## License and attribution
+## License and citation
 
 MIT, inherited from GroundCUA (see `LICENSE`). Screenshots show third-party
-applications whose interfaces remain the property of their owners.
+applications whose interfaces remain the property of their owners. If you use
+this data, please cite GroundCUA:
 
 ```bibtex
 @misc{feizi2025groundingcomputeruseagents,