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Update README.md

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@@ -6,8 +6,9 @@ GeoVistaBench is a collection of real-world photos with rich metadata for evalua
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  ## Dataset Structure
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- - `id`: unique identifier.
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  - `raw_image_path`: relative path (within this repo) to the source picture under `raw_image/<uid>/`.
 
 
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  - `preview`: compressed JPEG preview (<=1M pixels) under `preview_image/<uid>/`. This is used by HF Dataset Viewer.
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  - `metadata`: downstream users can parse it to obtain lat/lng, city names, multi-level location tags, and related information.
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  - `data_type`: string describing the imagery type.
@@ -23,8 +24,9 @@ All samples are stored in a Hugging Face-compatible parquet file.
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  ds = load_dataset('path/to/this/folder', split='test')
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  sample = ds[0]
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- ``
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- `sample["raw_image_path"]` points to the higher-quality file for inference.
 
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  ## Related Resources
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@@ -39,12 +41,12 @@ https://huggingface.co/datasets/LibraTree/GeoVistaBench
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  ## Citation
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  ```
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  @misc{wang2025geovistawebaugmentedagenticvisual,
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- title = {GeoVista: Web-Augmented Agentic Visual Reasoning for Geolocalization},
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- author = {Yikun Wang and Zuyan Liu and Ziyi Wang and Pengfei Liu and Han Hu and Yongming Rao},
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- year = {2025},
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- eprint = {2511.15705},
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- archivePrefix= {arXiv},
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- primaryClass = {cs.CV},
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- url = {https://arxiv.org/abs/2511.15705},
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  }
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  ```
 
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  ## Dataset Structure
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  - `raw_image_path`: relative path (within this repo) to the source picture under `raw_image/<uid>/`.
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+ - `id`: unique identifier.
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+ - `prompt`: textual user query.
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  - `preview`: compressed JPEG preview (<=1M pixels) under `preview_image/<uid>/`. This is used by HF Dataset Viewer.
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  - `metadata`: downstream users can parse it to obtain lat/lng, city names, multi-level location tags, and related information.
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  - `data_type`: string describing the imagery type.
 
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  ds = load_dataset('path/to/this/folder', split='test')
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  sample = ds[0]
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+ ```
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+
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+ **sample["raw_image_path"]` points to the higher-quality image for inference.**
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  ## Related Resources
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  ## Citation
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  ```
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  @misc{wang2025geovistawebaugmentedagenticvisual,
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+ title={GeoVista: Web-Augmented Agentic Visual Reasoning for Geolocalization},
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+ author={Yikun Wang and Zuyan Liu and Ziyi Wang and Han Hu and Pengfei Liu and Yongming Rao},
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+ year={2025},
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+ eprint={2511.15705},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.CV},
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+ url={https://arxiv.org/abs/2511.15705},
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  }
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  ```