Update dataset card: Add task categories, language, and populate paper/GitHub links

README.md

@@ -1,4 +1,8 @@
 ---
+task_categories:
+- image-text-to-text
+language:
+- en
 dataset_info:
 - config_name: attribute_grounding_and_alignment
   features:
@@ -90,7 +94,7 @@ configs:
 ---
 
 ## 📊 ChartAlignBench
-[**📖 Paper**]() | [**💻 GitHub**]()
+[**📖 Paper**](https://huggingface.co/papers/2510.26781) | [**💻 GitHub**](https://github.com/tianyi-lab/ChartAlignBench)
 
 ChartAlignBench is a multi-modal benchmark designed to evaluate vision-language models (VLMs) on dense-level chart grounding and multi-chart alignment to comprehensively assess fine-grained chart understanding in VLMs. 
 
@@ -112,7 +116,7 @@ ChartAlignBench contains 9K+ instances, divided into three evaluation subsets:-
 
 For each subset, the test*.parquet files contain the annotations and image pairs pre-loaded for processing with HF Datasets.
 
-```
+```python
 from datasets import load_dataset
 
 data_grounding_and_alignment_subset = load_dataset("umd-zhou-lab/ChartAlignBench", "data_grounding_and_alignment")
@@ -154,5 +158,4 @@ robustness_subset = load_dataset("umd-zhou-lab/ChartAlignBench", "robustness")
 | set_idx | Set index which groups the 5 chart pairs in a robustness set |
 | set_pair_idx | Pair index within a set (1-5) |
 |num_cell_difference | Number of data points which differ between the chart pair |
-|attribute_varied | Attribute which varies across the 5 chart pairs |
-
+|attribute_varied | Attribute which varies across the 5 chart pairs |