Rename task names and reorder to Task_A/B/C in README

FlattenFold -> Task_A, TeeShirtSort -> Task_B, HangCloth -> Task_C.
Reordered all sections to follow Task_A, Task_B, Task_C order.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

README.md

@@ -6,7 +6,7 @@ tags:
 - LeRobot
 configs:
 - config_name: default
-  data_files: FlattenFold/base/data/chunk-000/episode_000000.parquet
+  data_files: Task_A/base/data/chunk-000/episode_000000.parquet
 ---
 # KAI0
 <div align="center">
@@ -36,28 +36,28 @@ configs:
 ## [About the Dataset](#contents)
 - **~134 hours** real world scenarios 
 - **Main Tasks**
-    - ***FlattenFold***  
+    - ***Task_A***
       - Single task
       - Initial state: T-shirts are randomly tossed onto the table, presenting random crumpled configurations
       - Manipulation task: Operate the robotic arm to unfold the garment, then fold it
-    - ***HangCloth***
-      - Single task
-      - Initial state: Hanger is randomly placed, garment is randomly positioned on the table
-      - Manipulation task: Operate the robotic arm to thread the hanger through the garment, then hang it on the rod
-    - ***TeeShirtSort***
+    - ***Task_B***
       - Garment classification and arrangement task
       - Initial state: Randomly pick a garment from the laundry basket
       - Classification: Determine whether the garment is a T-shirt or a dress shirt
       - Manipulation task:
         - If it is a T-shirt, fold the garment
         - If it is a dress shirt, expose the collar, then push it to one side of the table
+    - ***Task_C***
+      - Single task
+      - Initial state: Hanger is randomly placed, garment is randomly positioned on the table
+      - Manipulation task: Operate the robotic arm to thread the hanger through the garment, then hang it on the rod
 - **Count of the dataset** 
 
     | Task | Base (episodes count/hours) | DAgger (episodes count/hours) | Total(episodes count/hours) |
     |------|-----------------------------|-------------------------------|-----------------------------|
-    | FlattenFold | 3,055/~42 hours             | 3,457/ ~13 Hours              | 6,512 /~55 hours            | 
-    | HangCloth | 6954/~61 hours              | 686/~12 hours                 | 7640/~73 hours              |
-    | TeeShirtSort | 5988/~31 hours              | 769/~22 hours                 | 6757/~53 hours              |
+    | Task_A | 3,055/~42 hours             | 3,457/ ~13 Hours              | 6,512 /~55 hours            |
+    | Task_B | 5988/~31 hours              | 769/~22 hours                 | 6757/~53 hours              |
+    | Task_C | 6954/~61 hours              | 686/~12 hours                 | 7640/~73 hours              |
     | **Total** | **15,997/~134 hours**       | **4,912/~47 hours**           | **20,909/~181 hours**       |
 
 ## [Load the dataset](#contents)
@@ -148,7 +148,7 @@ Under each task directory, data is partitioned into two subsets: base and dagger
   contains on-policy recovery trajectories collected via iterative DAgger, designed to populate failure recovery modes absent in static demonstrations.
 ```text
 Kai0-data/
-├── FlattenFold/
+├── Task_A/
 │   ├── base/
 │   │   ├── data/
 │   │   │   ├── chunk-000/
@@ -178,10 +178,10 @@ Kai0-data/
 │   │       ├── tasks.jsonl
 │   │       └── episodes_stats.jsonl
 │   └── dagger/
-├── HangCloth/
+├── Task_B/
 │   ├── base/
 │   └── dagger/
-├── TeeShirtSort/
+├── Task_C/
 │   ├── base/
 │   └── dagger/
 └── README.md
@@ -301,7 +301,7 @@ the basic struct of the [info.json](#meta/info.json)
 | index | [N, 1] | Global unique index across all frames in the dataset |
 | task_index | [N, 1] | Index identifying the task type being performed |
 
-### [tasks.jsonl](#FlattenFold/meta/tasks.jsonl)
+### [tasks.jsonl](#Task_A/meta/tasks.jsonl)
 Contains task language prompts (natural language instructions) that specify the manipulation task to be performed. Each entry maps a task_index to its corresponding task description, which can be used for language-conditioned policy training.
 
 # License and Citation