Link the public CC BY 4.0 LingBot training dataset

README.md

@@ -62,12 +62,12 @@ WORL trains policies using autoregressive rollouts, reward evaluation,
 candidate selection and policy updates. The project's LingBot reference
 configuration combines HPSv3, NVRM and VGGT-Omega PI Camera rewards.
 
-The team supplied an [OpenScene/revisit training bundle](https://huggingface.co/datasets/qyoo/lingbot-top2400-training-data)
+The team supplied [WORL-Lingbot-Training-Data](https://huggingface.co/datasets/Efficient-Large-Model/WORL-Lingbot-Training-Data), an OpenScene/revisit training bundle
 containing 2,218 records with prompts, initial frames and camera-conditioning
 arrays. Initial scene imagery was generated using gpt-image. This describes
 the supplied project dataset and reference configuration; the exported model
 does not record an exact per-run dataset/configuration binding. The training
-dataset is distributed separately from these weights.
+dataset is distributed separately under CC BY 4.0.
 
 ## Download and load
 

RELEASE_MANIFEST.json

@@ -27,8 +27,8 @@
     },
     {
       "path": "README.md",
-      "size_bytes": 4884,
-      "sha256": "33507fb8cc826f364239a04039add527bfe5da82094e31cb32ff8925eb6e5868"
+      "size_bytes": 4923,
+      "sha256": "10a1bb0296a1c966c773cd0c688d91b7ab25d668ef41ae353f7b695b71c41dd7"
     },
     {
       "path": "adapter_config.json",