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  ---
 
 
 
 
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  tags:
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- - gui-agents
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  - world-model
 
 
 
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  ---
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  # LGWM data
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- Processed transitions used to train and evaluate LGWM.
 
 
 
 
 
 
 
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  | Path | Content |
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  | --- | --- |
@@ -14,11 +27,13 @@ Processed transitions used to train and evaluate LGWM.
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  | `index/` | Transition indexes for each source and split |
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  | `text_table.npz` | Action-text embeddings |
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  Sources:
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  [AITW](https://github.com/google-research/google-research/tree/master/android_in_the_wild),
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  [AndroidControl](https://github.com/google-research/google-research/tree/master/android_control),
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  [GUIOdyssey](https://huggingface.co/datasets/OpenGVLab/GUI-Odyssey),
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  [AMEX](https://huggingface.co/datasets/Yuxiang007/AMEX) and
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  [MiniWoB++](https://github.com/Farama-Foundation/miniwob-plusplus).
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-
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- Code and usage: https://github.com/jiamingzhang94/lgwm
 
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  ---
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+ task_categories:
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+ - image-feature-extraction
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+ size_categories:
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+ - 1M<n<10M
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  tags:
 
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  - world-model
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+ - gui-agent
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+ - computer-use
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+ - agent-safety
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  ---
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  # LGWM data
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+ Processed GUI transitions used to train and evaluate
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+ [LGWM](https://huggingface.co/jiamingzz/lgwm), the latent world model from
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+ **Right Screen, Wrong Transition: World Models as Verifiers for GUI Agents**.
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+ Each transition is a before screenshot, an action and an after screenshot.
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+
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+ [Code](https://github.com/jiamingzhang94/lgwm) · [Model weights](https://huggingface.co/jiamingzz/lgwm)
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+
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+ The corpus has 1,824,824 training and 20,835 validation transitions.
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  | Path | Content |
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  | --- | --- |
 
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  | `index/` | Transition indexes for each source and split |
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  | `text_table.npz` | Action-text embeddings |
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+ ```bash
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+ hf download jiamingzz/lgwm-data --repo-type dataset --local-dir data
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+ ```
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+
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  Sources:
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  [AITW](https://github.com/google-research/google-research/tree/master/android_in_the_wild),
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  [AndroidControl](https://github.com/google-research/google-research/tree/master/android_control),
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  [GUIOdyssey](https://huggingface.co/datasets/OpenGVLab/GUI-Odyssey),
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  [AMEX](https://huggingface.co/datasets/Yuxiang007/AMEX) and
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  [MiniWoB++](https://github.com/Farama-Foundation/miniwob-plusplus).