Update README.md

README.md

@@ -35,15 +35,35 @@ configs:
     path: data/en-*
   - split: zh
     path: data/zh-*
+license: mit
+task_categories:
+- visual-question-answering
+language:
+- en
+- zh
+tags:
+- chemistry
 ---
 
-# RxnBench: Benchmark Dataset for Chemical Reaction Figure Comprehension
+# RxnBench: Benchmark for Chemical Reaction Figure Understanding
 
-We curated a dataset of 305 figures related to organic chemical reactions, selected from multiple high-impact OpenAssess journals. In total, it contains **1,525 question–answer pairs**. For each figure, domain experts designed five multiple-choice VQA questions focused on chemical reaction figure understanding, which were refined through several rounds of rigorous review and revision.
 
-Answering these questions requires expertise equivalent to a Ph.D. level in organic chemistry or higher.
+## 📘 Benchmark Summary
 
-The benchmark is available in both English and Chinese versions.
+RxnBench is a visual question answering (VQA) benchmark comprising 1,525 multiple-choice questions (MCQs) at the PhD-level of organic chemistry reaction understanding.
+
+The benchmark is built from 305 scientific figures drawn from high-impact OpenAssess journals. 
+For each figure, domain experts carefully designed five multiple-choice VQA questions targeting the interpretation of organic reaction diagrams. 
+These questions were further refined through multiple rounds of rigorous review and revision to ensure both clarity and scientific accuracy. 
+The questions cover a variety of types, including the description of chemical reaction images, extraction of reaction content, recognition of molecules or Markush structures, and determination of mechanisms.
+This benchmark challenges visual-language models on their foundational knowledge of organic chemistry, multimodal contextual reasoning, and chemical reasoning skills.
+
+The benchmark is released in both English and Chinese versions.
+
+
+## 📊 Benchmark Leaderboard
+
+We evaluated several of the latest popular MLLMs, including both closed-source and open-source models.
 
 |  Moldel   | Weight | UpdateTime | RxnBench-En  | RxnBench-Zh |
 |----|:----:|:----:|:----:|:----:| 
@@ -57,3 +77,8 @@ The benchmark is available in both English and Chinese versions.
 | gpt-4o mini | Proprietary | 20240718  | 0.6636 | 0.6066 |
 | Choice longest answer | - | -| 0.426 | 0.452 |
 | Random | - | - | 0.250 | 0.250 |
+
+
+## 📖 Citation
+
+our paper coming soon ...