update readme

README.md

@@ -36,15 +36,10 @@ Please download the dataset accordingly.
 
 ##  📕 Table of Contents
 
-- [✨ File Origanization Structure](#filestructure)
-- [🍟 Usage](#usage)
-- [🌐 General-Bench](#bench)
-  - [🍕 Capabilities and Domians Distribution](#distribution)
-- [🖼️ Image Task Taxonomy](#imagetaxonomy)
-- [📽️ Video Task Taxonomy](#videotaxonomy)
-- [📞 Audio Task Taxonomy](#audiotaxonomy)
-- [💎 3D Task Taxonomy](#3dtaxonomy)
-- [📚 Language Task Taxonomy](#languagetaxonomy)
+- [✨ Scope-A](#scope_a)
+- [🌐 Scope-B](#scope_b)
+- [🖼️ Scope-C](#scope_c)
+- [📽️ Scope-D](#scope_d)
 
 
 
@@ -52,68 +47,22 @@ Please download the dataset accordingly.
 
 ---
  
-<span id='filestructure'/>
+<span id='scope_a'/>
 
-# ✨✨✨ **File Origanization Structure**
+# ✨✨✨ **Scope-A**
 
-Here is the organization structure of the file system:
+Full-spectrum leaderboard covering all modalities and tasks under General-Level, for highly capable, general-purpose multimodal models.
+
+- 🔍 Details:
+  - ✔️ Covers all General-Level tasks and modalities.
+  - ✔️ Most challenging track; requires high model capacity and resource commitment.
+
+- 🎉 Highlights:
+  - ✔️ Evaluates holistic generalization and cross-modal synergy.
+  - ✔️ Suitable for near-AGI or foundation-level multimodal generalists.
 
 ```
-General-Bench
-├── Image
-│   ├── comprehension
-│   │   ├── Bird-Detection
-│   │   │   ├── annotation.json
-│   │   │   └── images
-│   │   │       └── Acadian_Flycatcher_0070_29150.jpg
-│   │   ├── Bottle-Anomaly-Detection
-│   │   │   ├── annotation.json
-│   │   │   └── images
-│   │   └── ...
-│   └── generation
-│       └── Layout-to-Face-Image-Generation
-│           ├── annotation.json
-│           └── images
-│           └── ...
-├── Video
-│   ├── comprehension
-│   │   └── Human-Object-Interaction-Video-Captioning
-│   │       ├── annotation.json
-│   │       └── videos
-│   │       └── ...
-│   └── generation
-│       └── Scene-Image-to-Video-Generation
-│           ├── annotation.json
-│           └── videos
-│           └── ...
-├── 3d
-│   ├── comprehension
-│   │   └── 3D-Furniture-Classification
-│   │       ├── annotation.json
-│   │       └── pointclouds
-│   │       └── ...
-│   └── generation
-│       └── Text-to-3D-Living-and-Arts-Point-Cloud-Generation
-│           ├── annotation.json
-│           └── pointclouds
-│           └── ...
-├── Audio
-│   ├── comprehension
-│   │   └── Accent-Classification
-│   │       ├── annotation.json
-│   │       └── audios
-│   │       └── ...
-│   └── generation
-│       └── Video-To-Audio
-│           ├── annotation.json
-│           └── audios
-│           └── ...
-├── NLP
-│   ├── History-Question-Answering
-│   │   └── annotation.json
-│   ├── Abstractive-Summarization
-│   │   └── annotation.json
-│   └── ...
+
 
 ```
 
@@ -124,13 +73,6 @@ An illustrative example of file formats:
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/64c139d867eff857ea51caa8/RD3b7Jwu0dftVq-4KbpFr.png)
 
 
-<span id='usage'/>
-
-## 🍟🍟🍟 Usage 
-
-Please download all the files in this repository. We also provide overview.json, which is an example of the format of our dataset.
-
-For more instructions, please go to the [document page](https://generalist.top/document).
 
 
 ---
@@ -139,105 +81,166 @@ For more instructions, please go to the [document page](https://generalist.top/d
 
 
 
-<span id='bench'/>
+<span id='scope_b'/>
 
 
 
-# 🌐🌐🌐 **General-Bench** 
+# 🌐🌐🌐 Scope-B  
 
 
 
 
-A companion  massive multimodal benchmark dataset, encompasses a broader spectrum of skills, modalities, formats, and capabilities, including over **`700`** tasks and **`325K`** instances. 
-
-<div align="center">
-<img src='https://cdn-uploads.huggingface.co/production/uploads/647773a1168cb428e00e9a8f/d4TIWw3rlWuxpBCEpHYJB.jpeg'>
-<p> Overview of General-Bench, which covers 145 skills for more than 700 tasks with over 325,800 samples under
-comprehension and generation categories in various modalities</p>
-</div>
+Modality-specific leaderboards focusing on single modality or partially joint modality (e.g., image, video, audio, 3D) for modality-wise generalists.
 
+- 🔍 Details:
+  - ✔️ 7 separate leaderboards (4 single modality + 3 combined modality).
+  - ✔️ Focuses on mastering diverse tasks within a single modality.
 
-<span id='distribution'/>
 
-## 🍕🍕🍕 Capabilities and Domians Distribution
+- 🎉 Highlights:
+  - ✔️ Measures within-modality generalization.
+  - ✔️ Suited for intermediate-level models with cross-task transferability.
 
-<div align="center">
-<img src='https://cdn-uploads.huggingface.co/production/uploads/64c139d867eff857ea51caa8/fF3iH95B3QEBvJYwqzZVG.png'>
-<p> Distribution of various capabilities evaluated in General-Bench.</p>
-</div>
 
+In [Scope-B](https://huggingface.co/datasets/General-Level/General-Bench-Closeset-Scoped/tree/main/Scope-B), we provide the subset of data corresponding to each sub-leaderboard. Each task is represented by a separate JSON file, which specifies the dataset associated with that particular sub-leaderboard, including the relevant file names.
+All referenced data files can be found in the [👉 **`Close Set`**](https://huggingface.co/datasets/General-Level/General-Bench-Closeset) repository.
 
-<div align="center">
-<img src='https://cdn-uploads.huggingface.co/production/uploads/64c139d867eff857ea51caa8/wQvllVeK-KC3Edp8Zjh-V.png'>
-<p>Distribution of various domains and disciplines covered by General-Bench.</p>
-</div>
+```
+{  
+   ## paradigm
+  "comprehension": { 
+    ## skill name
+    "Speech Accent Understanding":   
+    [
+      {
+        ## task name：data file name in Closeset
+        "Accent Classification": "AccentClassification"   
+      },
+      {
+        "Accent Sex Classification": "AccentSexClassification"
+      },
+      {
+        "Speaker Identification": "SpeakerIdentification"
+      },
+      {
+        "Vocal Sound Classification": "VocalSoundClassification"
+      }
+    ],
+    ...
+  }
+}
 
+```
 
 
 
+----
 
-<span id='imagetaxonomy'/>
 
-# 🖼️ Image Task Taxonomy
-<div align="center">
-<img src='https://cdn-uploads.huggingface.co/production/uploads/64c139d867eff857ea51caa8/2QYihQRhZ5C9K5IbukY7R.png'>
-<p>Taxonomy and hierarchy of data in terms of Image modality.</p>
-</div>
 
 
 
+<span id='scope_c'/>
 
-<span id='videotaxonomy'/>
+# 🖼️🖼️🖼️ Scope-C
 
-# 📽️ Video Task Taxonomy
+Leaderboards categorized by comprehension vs. generation tasks within each modality. Lower entry barrier for early-stage or lightweight models.
 
-<div align="center">
-<img src='https://cdn-uploads.huggingface.co/production/uploads/64c139d867eff857ea51caa8/A7PwfW5gXzstkDH49yIG5.png'>
-<p>Taxonomy and hierarchy of data in terms of Video modality.</p>
-</div>
+- 🔍 Details:
+  - ✔️ 8 leaderboards: 2 × 4 for multimodal comprehension/generation under different modalities.
+  - ✔️ Supports entry-level model evaluation or teams with limited resources.
 
 
+- 🎉 Highlights:
+  - ✔️ Assesses task-type specialization: understanding or generation.
+  - ✔️ Reflects generalization across task types.
 
 
 
 
+In [Scope-C](https://huggingface.co/datasets/General-Level/General-Bench-Closeset-Scoped/tree/main/Scope-C), we provide the subset of data corresponding to each sub-leaderboard. Each task is represented by a separate JSON file, which specifies the dataset associated with that particular sub-leaderboard, including the relevant file names.
+All referenced data files can be found in the [👉 **`Close Set`**](https://huggingface.co/datasets/General-Level/General-Bench-Closeset) repository.
 
+```
+{
+    ## skill name
+  "3D Human-related Object Classification": [
+    {
+        ## task name：data file name in Closeset
+      "3D Accessory Classification": "3d_classification/ModelNet40/accessory"
+    },
+    {
+      "3D Appliance Classification": "3d_classification/ModelNet40/appliance"
+    },
+    {
+      "3D Tableware Classification": "3d_classification/ModelNet40/tableware"
+    },
+    {
+      "3D Musical Instrument Classification": "3d_classification/ModelNet40/musical_instrument"
+    },
+    {
+      "3D Person Classification": "3d_classification/ModelNet40/person"
+    }
+  ],
+  ...
+}
 
+```
 
-<span id='audiotaxonomy'/>
+----
 
-# 📞 Audio Task Taxonomy
 
+<span id='scope_d'/>
 
+# 📽️📽️📽️ Scope-D
 
-<div align="center">
-<img src='https://cdn-uploads.huggingface.co/production/uploads/64c139d867eff857ea51caa8/e-QBvBjeZy8vmcBjAB0PE.png'>
-<p>Taxonomy and hierarchy of data in terms of Audio modality.</p>
-</div>
+Fine-grained leaderboards focused on specific task clusters (e.g., VQA, Captioning, Speech Recognition), ideal for partial generalists.
 
+- 🔍 Details:
+  - ✔️ Large number of sub-leaderboards, each scoped to a skill set.
+  - ✔️ Easiest to participate; lowest cost.
 
 
-<span id='3dtaxonomy'/>
+- 🎉 Highlights:
+  - ✔️ Evaluates fine-grained skill performance.
+  - ✔️ Helps identify model strengths and specialization areas.
+  - ✔️ Encourages progressive development toward broader leaderboard participation.
 
-# 💎 3D Task Taxonomy
 
 
-<div align="center">
-<img src='https://cdn-uploads.huggingface.co/production/uploads/64c139d867eff857ea51caa8/EBXb-wyve14ExoLCgrpDK.png'>
-<p>Taxonomy and hierarchy of data in terms of 3D modality.</p>
-</div>
 
 
+In [Scope-D](https://huggingface.co/datasets/General-Level/General-Bench-Closeset-Scoped/tree/main/Scope-D), we provide subset datasets corresponding to each sub-leaderboard. Each task is represented by a JSON file named in the format:
+`{modality name}——{comp/gen}_{clustered skill name}.json`.
+Each JSON file specifies the dataset used for the corresponding sub-leaderboard task, including the list of relevant file names.
+All referenced data files can be found in the [👉 **`Close Set`**](https://huggingface.co/datasets/General-Level/General-Bench-Closeset) repository.
 
+```
+{   
+    ## clusered skill name
+  "Classifcation": {
+    ## skill name
+    "3D Human-related Object Classification": [
+      "3d_classification/ModelNet40/accessory",  ## data file name in Closeset
+      "3d_classification/ModelNet40/appliance",
+      "3d_classification/ModelNet40/tableware",
+      "3d_classification/ModelNet40/musical_instrument",
+      "3d_classification/ModelNet40/person"
+    ],
+    "3D Structure and Environment Classification": [
+      "3d_classification/ModelNet40/furniture",
+      "3d_classification/ModelNet40/structure"
+    ],
+    "Transportation and Technology Object Classification": [
+      "3d_classification/ModelNet40/electronic",
+      "3d_classification/ModelNet40/vehicle"
+    ]
+  }
+}
 
-<span id='languagetaxonomy'/>
+```
 
-# 📚 Language Task Taxonomy
 
-<div align="center">
-<img src='https://cdn-uploads.huggingface.co/production/uploads/64c139d867eff857ea51caa8/FLfk3QGdYb2sgorKTj_LT.png'>
-<p>Taxonomy and hierarchy of data in terms of Language modality.</p>
-</div>