Update README.md

README.md

@@ -53,7 +53,7 @@ configs:
 
 
 
-<h1 style="display: flex; align-items: center; justify-content: center; font-size: 1.70em; font-weight: 600;">
+<h1 style="display: flex; align-items: center; justify-content: center; font-size: 1.75em; font-weight: 600;">
 
 
   <img src="https://huggingface.co/datasets/BAAI/RefSpatial-Bench/resolve/main/assets/logo.png" style="height: 60px; flex-shrink: 0;">
@@ -202,7 +202,7 @@ You can load the dataset easily using the `datasets` library:
 ```python
 from datasets import load_dataset
 
-# Load the entire dataset (all splits: location, placement, unseen)
+# Load the entire dataset (all splits: location, placement)
 # This returns a DatasetDict
 dataset_dict = load_dataset("JingkunAn/RefSpatial-Expand-Bench")
 
@@ -234,7 +234,7 @@ print(f"Reasoning Steps (from HF Dataset): {sample['step']}")
 
 If you are working with the raw data format (e.g., after cloning the repository or downloading the raw files), you can load the questions from the `question.json` file for each split and then load the images and masks using a library like Pillow (PIL).
 
-This example assumes you have the `location`, `placement`, and `unseen` folders (each containing `image/`, `mask/`, and `question.json`) in a known `base_data_path`.
+This example assumes you have the `location` and  `placement` folders (each containing `image/`, `mask/`, and `question.json`) in a known `base_data_path`.
 
 ```python
 import json