Add paper and project page links

README.md

@@ -1,13 +1,18 @@
 ---
-license: apache-2.0
+annotations_creators:
+- expert-generated
 language:
 - en
+license: apache-2.0
 size_categories:
 - 10K<n<100K
+source_datasets:
+- original
 task_categories:
 - image-to-text
 - visual-question-answering
 - text-generation
+pretty_name: Diagram-MMU
 tags:
 - scientific-diagrams
 - diagram-understanding
@@ -19,11 +24,6 @@ tags:
 - chart-understanding
 - multimodal
 - benchmark
-pretty_name: Diagram-MMU
-annotations_creators:
-- expert-generated
-source_datasets:
-- original
 configs:
 - config_name: diagrams
   data_files:
@@ -138,7 +138,7 @@ dataset_info:
 
 **ECCV 2026**
 
-🏠 Homepage *(coming soon)* · 💻 [Code](https://github.com/AIGrounding/Diagram-MMU) · 📄 Paper *(coming soon)*
+🏠 [Project Page](https://vi-ocean.github.io/projects/diagram-mmu) · 💻 [Code](https://github.com/AIGrounding/Diagram-MMU) · 📄 [Paper](https://huggingface.co/papers/2608.12262)
 
 **Diagram-MMU** is a benchmark for evaluating Multimodal Large Language Models (MLLMs) on understanding, parsing, and editing **scientific diagrams**. It contains **3,744** curated diagrams (each with compilable source code) and **18,305** human-validated evaluation instances across **six domains** (`charts`, `planar_geometry`, `3d_shapes`, `graph_structures`, `chemistry`, `circuit_diagrams`), over three tasks: diagram-to-code parsing (**D2C-P**), diagram-to-code editing (**D2C-E**), and diagram question answering (**DQA**).
 
@@ -194,4 +194,4 @@ Released under the **Apache License 2.0**. Source code is collected from officia
   journal = {arXiv preprint arXiv:TODO},
   year    = {2026}
 }
-```
+```