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- ---
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- license: cc-by-sa-4.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ <<<<<<< HEAD
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+ ---
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+ license: cc-by-sa-4.0
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+ ---
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+ =======
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+ # FunUI Benchmark
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+
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+ ## 📖 Introduction
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+ **FunUI** is a bilingual benchmark designed to fill the gap of comprehensive evaluation datasets in the field of **screen understanding**.
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+ It encompasses **four fundamental tasks** and provides a holistic evaluation platform to assess models’ abilities on mobile UI comprehension.
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+
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+ ---
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+
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+ ## ✨ Key Features
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+
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+ - **Bilingual**
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+ - Includes **2,150 Chinese screens** and **9,347 English screens** from Android devices.
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+ - Annotated with about **14k Chinese samples** and **18k English samples**.
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+ - The **first benchmark** that enables systematic evaluation of **both Chinese and English screen understanding**.
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+
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+ - **Comprehensive**
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+ - Covers multiple dimensions of screen understanding:
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+ - **UI Grounding** (element localization)
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+ - **UI Referring** (element identification)
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+ - **Screen Question Answering**
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+ - **Screen Summarization**
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+ - Ranges from spatial grounding and entity recognition to integrated analysis of screen content.
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+
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+ - **Diverse**
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+ - Provides QA pairs involving **120+ icons and widgets**.
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+ - Includes **complex reasoning questions** related to element relations, attributes, arithmetic, and more.
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+ - Poses greater challenges compared to commonly used OCR-related tasks.
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+
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+ ---
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+
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+ ## 📊 Tasks
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+
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+ 1. **UI Grounding**
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+ - Models are required to localize the target UI element.
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+
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+ 2. **UI Referring**
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+ - Models identify the specific UI element referred to in text.
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+
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+ 3. **Screen Question Answering**
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+ - Models answer diverse questions about screen content.
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+
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+ 4. **Screen Summarization**
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+ - Models generate concise summaries of the screen.
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+
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+ ---
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+
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+ ## 🚀 Applications
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+ - Automated **UI comprehension** and interaction.
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+ - Development of **intelligent assistants** and mobile automation.
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+ - **Benchmarking multimodal models** for screen understanding.
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+
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+
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+ ---
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+
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+ ## 📜 Citation
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+ If you use **FunUI** benchmark in your research, please cite our paper:
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+
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+ ```bibtex
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+ @article{202408.2137,
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+ title = {UI-Hawk: Unleashing the Screen Stream Understanding for GUI Agents},
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+ author = {Jiwen Zhang and Yaqi Yu and Minghui Liao and Wentao Li and Jihao Wu and Zhongyu Wei},
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+ doi = {10.20944/preprints202408.2137.v1},
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+ url = {https://doi.org/10.20944/preprints202408.2137.v1},
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+ year = 2024,
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+ month = {August},
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+ publisher = {Preprints},
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+ journal = {Preprints}
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+ }
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+ ```
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+
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