Update README.md

README.md

@@ -15,9 +15,9 @@ It consists of the following components:
 
 - **object_affordance_prediction_absxy_561K.json**: 561K object affordance prediction QA pairs for 45,790 images sourced from [PACO-LVIS](https://github.com/facebookresearch/paco)
 
-- **object_ref_max_points_10_absxy_347K.json**: 347K object reference QA pairs for 287,956 images sourced from [RoboPoint](https://huggingface.co/datasets/wentao-yuan/robopoint-data)
+- **object_ref_max_points_10_absxy_347K.json**: 347K object reference QA pairs for 287,956 images sourced from [RoboPoint-data](https://huggingface.co/datasets/wentao-yuan/robopoint-data)
 
-- **region_ref_max_points_10_absxy_320K.json**: 320K region reference QA pairs for 270,182 images sourced from [RoboPoint](https://huggingface.co/datasets/wentao-yuan/robopoint-data)
+- **region_ref_max_points_10_absxy_320K.json**: 320K region reference QA pairs for 270,182 images sourced from [RoboPoint-data](https://huggingface.co/datasets/wentao-yuan/robopoint-data)
 
 # Dataset Format
 Each json file contains a list of structured conversations with image references. The QA pairs follows the format:
@@ -47,4 +47,4 @@ Each json file contains a list of structured conversations with image references
 ```
 
 # Evaluation
-For benchmarking protocols and evaluation metrics, please refer to **[RoboAfford-Eval](https://huggingface.co/datasets/tyb197/RoboAfford-Eval)** and [https://github.com/tyb197/RoboAfford](https://github.com/tyb197/RoboAfford) for more detailed information.
+For benchmarking protocols and evaluation metrics, please refer to [RoboAfford-Eval](https://huggingface.co/datasets/tyb197/RoboAfford-Eval) and [https://github.com/tyb197/RoboAfford](https://github.com/tyb197/RoboAfford) for more detailed information.