Add task category and improve dataset card

This PR adds the `robotics` task category to the dataset metadata and improves the dataset card with a brief description of the RoboFollow benchmark and links to the paper, code repository, and project page.

README.md

@@ -1,3 +1,15 @@
-## Paper
+---
+task_categories:
+- robotics
+---
 
-[RoboFollow: Unveiling the Instruction Following Mirage in Embodied Agents](https://arxiv.org/abs/2609.25636)
+# RoboFollow: Unveiling the Instruction Following Mirage in Embodied Agents
+
+This dataset is part of the **RoboFollow** benchmark, designed to evaluate instruction-following capabilities of embodied agents in manipulation tasks. Built on [RoboTwin](https://github.com/RoboTwin-Platform/RoboTwin), it provides shared-scene task configurations where multiple tasks coexist, requiring policies to rely on language to disambiguate objectives.
+
+The dataset includes expert demonstrations and evaluation tasks across four scene families, covering spatial relations, object attributes, trajectory constraints, and conditional instructions. It supports the benchmark's hierarchical evaluation protocol (L0–L3) to separate intent comprehension from physical execution.
+
+For more details, refer to:
+- Paper: [arXiv:2609.25636](https://arxiv.org/abs/2609.25636)
+- Project page: [RoboFollow Project](https://mrc-crm.github.io/RoboFollow/)
+- Code: [GitHub Repository](https://github.com/AutoLab-SAI-SJTU/RoboFollow)