| # OSReward Data Card |
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|
| ## Dataset Summary |
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|
| OSReward contains multimodal examples for outcome judgment of GUI-agent |
| trajectories across desktop, web, and mobile environments. Each example |
| provides a user request, selected screenshots, and, depending on the source, |
| textual action history or a task-specific rubric. The target is an |
| evidence-based assessment ending with `Judge: SUCCESS` or `Judge: FAIL`. |
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|
| ## Released Configurations |
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| ### Supervised fine-tuning |
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|
| - Exactly 100,000 judge instances from 16 source datasets. |
| - 359,789 unique screenshots. |
| - 58,712 SUCCESS labels and 41,288 FAIL labels. |
| - LLaMAFactory-compatible ShareGPT records. |
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| ### Reinforcement learning |
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|
| - Approximately 3K training examples. |
| - Approximately 200 validation examples. |
| - Parquet records compatible with the common verl multimodal data schema. |
| - Screenshots are referenced from the SFT image package and are not embedded |
| in parquet. |
|
|
| ## Publication Safety Filter |
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| 7 records and 29 screenshots in credential-bearing connected components were excluded before publication. This prevents literal API tokens or private-key material found in source GUI tasks from being released. |
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| ## Intended Use |
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| The data is intended for research on multimodal GUI trajectory evaluation, |
| supervised reward-model training, and rule-reward RL. Users should validate |
| format assumptions, data rights, and suitability for their own deployment. |
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| ## Limitations |
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| - Labels are outcome judgments derived from heterogeneous GUI tasks and may |
| contain annotation errors or ambiguous cases. |
| - Platform, task, label, and prompt-style distributions are not uniform. |
| - Screenshots may contain content rendered by third-party applications or |
| websites. |
| - The RL split emphasizes difficult and informative cases and should not be |
| treated as an unbiased sample of all GUI interactions. |
| - Framework and model support for long-context multimodal MoE training is |
| version-sensitive and should be validated in the user's own environment. |
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| No standalone license is specified in this initial release. Users are |
| responsible for determining the rights and restrictions that apply to their |
| use of the records and screenshot content. |
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|
| ## WebTrail Supplement |
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|
| The WebTrail increment contains 6,386 strict-unanimous SFT instances from |
| 6,386 unique web trajectories. Each instance uses the last up to five visual |
| states and retains a GPT-5.5 reasoning target; three judge verdicts are kept in |
| `results`. These rows complete the SFT release to 100,000 judge instances. |
| This count is not a claim of 100,000 unique underlying trajectories because |
| some original-release trajectories have multiple screenshot or prompt views. |
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