Add model card for GUI-AIMA-3B

README.md

@@ -0,0 +1,48 @@
+---
+library_name: transformers
+pipeline_tag: image-text-to-text
+base_model: Qwen/Qwen2.5-VL-3B-Instruct
+---
+
+# GUI-AIMA-3B
+
+GUI-AIMA (Aligning Intrinsic Multimodal Attention) is an attention-based and coordinate-free supervised fine-tuning framework for efficient GUI grounding, as introduced in the paper [GUI-AIMA: Aligning Intrinsic Multimodal Attention with a Context Anchor for GUI Grounding](https://huggingface.co/papers/2511.00810).
+
+The model aligns the intrinsic multimodal attention of Multimodal Large Language Models (MLLMs) with patch-wise grounding signals. This approach is highly data-efficient and allows for the integration of a plug-and-play zoom-in stage for high-resolution grounding without additional fine-tuning.
+
+## Model Details
+
+- **Architecture:** Based on Qwen2.5-VL-3B-Instruct with a context anchor mechanism for attention-based grounding.
+- **Task:** GUI Grounding (mapping instructions to actionable screen regions).
+- **Paper:** [GUI-AIMA: Aligning Intrinsic Multimodal Attention with a Context Anchor for GUI Grounding](https://huggingface.co/papers/2511.00810)
+- **GitHub Repository:** [https://github.com/sjz5202/GUI-AIMA](https://github.com/sjz5202/GUI-AIMA)
+
+## Performance
+
+GUI-AIMA-3B achieves state-of-the-art performance among 3B-parameter models on several GUI grounding benchmarks:
+
+| Benchmark | Accuracy (1-step) | Accuracy (2-step Zoom-in) |
+|---|---|---|
+| ScreenSpot-Pro | 53.8% | 61.5% |
+| OSWorld-G | 62.8% | 68.1% |
+| ScreenSpot-v2 | 92.1% | - |
+| MMBench-GUI-L2 | 79.1% | - |
+| UI-Vision | 60.0% | - |
+
+## Usage
+
+The model requires custom code from the official repository for inference. Please refer to the [GitHub repository](https://github.com/sjz5202/GUI-AIMA) for installation instructions and example scripts (e.g., `eval/example_inference.py`).
+
+## Citation
+
+```bibtex
+@misc{zhou2025guiaimaaligningintrinsicmultimodal,
+      title={GUI-AIMA: Aligning Intrinsic Multimodal Attention with a Context Anchor for GUI Grounding}, 
+      author={Shijie Zhou and Viet Dac Lai and Hao Tan and Jihyung Kil and Wanrong Zhu and Changyou Chen and Ruiyi Zhang},
+      year={2025},
+      eprint={2511.00810},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={https://arxiv.org/abs/2511.00810}, 
+}
+```