Improve dataset card: Add metadata, paper and code links, and English summary

README.md

@@ -1,3 +1,22 @@
+---
+task_categories:
+- image-text-to-text
+language:
+- zh
+tags:
+- benchmark
+- vlm
+- graphic-reasoning
+- intelligence-test
+---
+
+This repository contains **ReasonBench**, a novel benchmark designed to evaluate Visual Language Models (VLMs) on complex graphic reasoning tasks. It comprises 1,613 questions derived from real-world intelligence tests, covering reasoning dimensions related to location, attribute, quantity, and multi-element tasks. ReasonBench provides a comprehensive framework for assessing VLMs' spatial, relational, and abstract reasoning capabilities.
+
+Paper: [Oedipus and the Sphinx: Benchmarking and Improving Visual Language Models for Complex Graphic Reasoning](https://huggingface.co/papers/2508.00323)
+Code and Data: https://github.com/ReasonBench/ReasonBench
+
+---
+
 ## ReasonBench：用于复杂图形推理的视觉语言模型评估基准
 
 ReasonBench 旨在评估视觉语言模型（VLMs）在复杂图形推理中的表现。数据集包含从真实智力测试中收集的 1,613 个问题，覆盖 11 个核心认知推理维度和 29 种任务类型，为评估 VLMs 的空间、关系和抽象推理能力提供综合框架。
@@ -45,4 +64,4 @@ ReasonBench 旨在评估视觉语言模型（VLMs）在复杂图形推理中的
 
 为未来研究者方便复现以及后续研究，我们将所有格式的图片url全部公开，分别对应题目，4-8个选项，题目➕选项。
 
-同时，我们公开了人类基准的准确率。
+同时，我们公开了人类基准的准确率。