Update VPB dataset card links

README.md

@@ -14,7 +14,7 @@ license: other
 
 **A video-language benchmark for process-level robot task progress estimation.**
 
-[Code](https://github.com/InternRobotics/VLAC-Cut) · [Paper](<PAPER_URL>) · [VLAC-Cut Model](https://huggingface.co/InternRobotics/VLAC-Cut)
+[Paper](https://arxiv.org/abs/2607.09776) · [Code](https://github.com/InternRobotics/VLAC-cut) · [Model](https://huggingface.co/InternRobotics/VLAC-Cut) · [Benchmark](https://huggingface.co/datasets/InternRobotics/VLAC-Cut-Benchmark)
 
 The **Video Progress Benchmark (VPB)** evaluates whether a model can estimate how a robot task evolves throughout a video, not only whether the final frame looks successful. VPB is built from the held-out portion of the **Progress Annotation Dataset** and explicitly tests advancement, stagnation, regression, and recovery.
 
@@ -112,8 +112,8 @@ Resolve this prefix to the absolute extracted-frame directory when running the G
 Detailed running commands and the complete metric implementation are provided in the GitHub repository:
 
 ```bash
-git clone https://github.com/InternRobotics/VLAC-Cut
-cd VLAC-Cut
+git clone https://github.com/InternRobotics/VLAC-cut
+cd VLAC-cut
 
 python scripts/evaluate_vpb_predictions.py \
   --benchmark-root /path/to/VLAC-Cut-Benchmark/splits \

data/README.md

@@ -1,10 +0,0 @@
-# Video Archives
-
-The Hugging Face dataset repository hosts the benchmark video archives under this directory:
-
-```text
-data/train_videos.tar
-data/test_videos.tar
-```
-
-These archives are intentionally not duplicated in the GitHub code repository. Download the dataset from Hugging Face and unpack the required archive before running the frame extraction tools.