Update README.md

README.md

@@ -59,15 +59,14 @@ configs:
   <img src="https://huggingface.co/datasets/BAAI/RefSpatial-Bench/resolve/main/assets/logo.png" style="height: 60px; flex-shrink: 0;">
 
   <span style="line-height: 1.2; margin-left: 0px; text-align: center;">
-    RefSpatial-Bench: A Benchmark for Multi-step Spatial Referring
+    RefSpatial-Expand-Bench: A Benchmark for Multi-step Spatial Referring
   </span>
 
 </h1>
 
+<!-- # RefSpatial-Expand-Bench: A Benchmark for Multi-step Spatial Referring with Reasoning -->
 
-<!-- # RefSpatial-Bench: A Benchmark for Multi-step Spatial Referring with Reasoning -->
-
- <!-- [![Generic badge](https://img.shields.io/badge/🤗%20Datasets-BAAI/RefSpatial--Bench-blue.svg)](https://huggingface.co/datasets/BAAI/RefSpatial-Bench)  -->
+ <!-- [![Generic badge](https://img.shields.io/badge/🤗%20Datasets-BAAI/RefSpatial--Expand--Bench-blue.svg)](https://huggingface.co/datasets/JingkunAn/RefSpatial-Expand-Bench)  -->
 
 <p align="center">
   <a href="https://zhoues.github.io/RoboRefer"><img src="https://img.shields.io/badge/%F0%9F%8F%A0%20Project-Homepage-blue" alt="HomePage"></a>
@@ -83,7 +82,7 @@ configs:
 
 
 
-Welcome to **RefSpatial-Bench**, a challenging benchmark based on real-world cluttered scenes to evaluate more complex multi-step spatial referring with reasoning.
+Welcome to **RefSpatial-Expand-Bench**, a challenging benchmark based on real-world cluttered scenes to evaluate more complex multi-step spatial referring with reasoning.
 
 <img src="https://api.visitorbadge.io/api/combined?path=https%3A%2F%2Fzhoues.github.io&labelColor=%232ccce4&countColor=%230158f9" alt="visitor badge" style="display: none;" />
 <img src="https://api.visitorbadge.io/api/combined?path=https%3A%2F%2Fanjingkun.github.io&labelColor=%232ccce4&countColor=%230158f9" alt="visitor badge" style="display: none;" />
@@ -132,14 +131,13 @@ We provide two formats:
 
 * `location`
 * `placement`
-* `unseen`
 
 Each sample includes:
 
 | Field    | Description                                                  |
 | :------- | :----------------------------------------------------------- |
 | `id`     | Unique integer ID                                            |
-| scene    | indoor or outdoor                                            |
+| `scene`  | Indoor or outdoor                                            |
 | `object` | Natural language description of target (object or free area), which is extracted from the `prompt` |
 | `prompt` | Full Referring expressions                                   |
 | `suffix` | Instruction for answer formatting (**different models may use different suffixes or none**; we provide the format used by RoboRefer) |
@@ -157,7 +155,6 @@ For full reproducibility and visualization, we also include the original files u
 
 * `Location/`
 * `Placement/`
-* `Unseen/`
 
 Each folder contains:
 
@@ -180,7 +177,7 @@ Each entry in `question.json` has the following format:
   "mask_path": "mask/40.png",
   "category": "location",
   "step": 2,
-  "scene": indoor
+  "scene": "indoor"
 }
 ```
 
@@ -190,10 +187,10 @@ Each entry in `question.json` has the following format:
 ## 🚀 How to Use RefSpaital-Bench
 
 
-<!-- This section explains different ways to load and use the RefSpatial-Bench dataset. -->
+<!-- This section explains different ways to load and use the RefSpatial-Expand-Bench dataset. -->
 
 The official evaluation code is available at https://github.com/Zhoues/RoboRefer.
-The following provides a quick guide on how to load and use the RefSpatial-Bench.
+The following provides a quick guide on how to load and use the RefSpatial-Expand-Bench.
 
 
 <details>
@@ -207,13 +204,13 @@ from datasets import load_dataset
 
 # Load the entire dataset (all splits: location, placement, unseen)
 # This returns a DatasetDict
-dataset_dict = load_dataset("BAAI/RefSpatial-Bench")
+dataset_dict = load_dataset("JingkunAn/RefSpatial-Expand-Bench")
 
 # Access a specific split, for example 'location'
 location_split_hf = dataset_dict["location"]
 
 # Or load only a specific split directly (returns a Dataset object)
-# location_split_direct = load_dataset("BAAI/RefSpatial-Bench", name="location")
+# location_split_direct = load_dataset("JingkunAn/RefSpatial-Expand-Bench", name="location")
 
 # Access a sample from the location split
 sample = location_split_hf[0] 
@@ -291,7 +288,7 @@ else:
 <summary><strong>Evaluating RoboRefer / RoboPoint</strong></summary>
 
 
-To evaluate RoboRefer on RefSpatial-Bench:
+To evaluate RoboRefer on RefSpatial-Expand-Bench:
 
 1. **Prepare Input Prompt:** 
 
@@ -346,7 +343,7 @@ To evaluate RoboRefer on RefSpatial-Bench:
 
 
 
-To evaluate Gemini Series on RefSpatial-Bench:
+To evaluate Gemini Series on RefSpatial-Expand-Bench:
 
 1. **Prepare Input Prompt:** 
 
@@ -478,7 +475,7 @@ Detailed statistics on `step` distributions and instruction lengths are provided
 
 ## 🏆 Performance Highlights
 
-Detailed accuracy results of RoboRefer-2B-SFT and RoboRefer-8B-SFT Models on RefSpatial-Bench-Expand
+Detailed accuracy results of RoboRefer-2B-SFT and RoboRefer-8B-SFT Models on RefSpatial-Expand-Bench
 
 #### **Location Task**