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README.md

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-license: cc-by-4.0
-language:
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+---
+license: cc-by-4.0
+language:
+- zh
+---
+# LLM Evaluation Benchmark for Chinese Language Teaching (CLTE)
+
+A comprehensive benchmark for evaluating large language models' capabilities as Chinese language teachers, consisting of three core evaluation dimensions.
+
+## Task Overview
+
+### Task 1: Basic Knowledge Evaluation
+- **Objective:** Assess foundational knowledge essential for international Chinese education
+- **Coverage:** 32 sub-topics across 5 major categories:
+  - Linguistics (307 questions)
+  - Chinese Culture (321 questions)
+  - Pedagogy (163 questions)
+  - World Culture (192 questions)
+  - Cross-cultural Communication (217 questions)
+- **Total:** 1,200 questions evaluating fundamental knowledge base
+
+### Task 2: International Teacher Examination
+- **Objective:** Evaluate comprehensive teaching literacy using authentic certification materials
+- **Data Source:** Real-world test questions from official International Chinese Language Teacher Certification exams
+- **Format:** Instructional passages accompanied by 2-10 single-choice questions (1,044 total questions)
+- **Focus:** Integrated linguistic and pedagogical reasoning in practical teaching scenarios
+
+### Task 3: Teaching Practice Evaluation
+- **Objective:** Measure instructional effectiveness through simulated teaching interactions
+- **Methodology:**
+  - Teacher models generate educational content from 120 teaching materials and guidelines
+  - Student models are tested before and after receiving instruction
+  - Effectiveness measured by performance improvement (120 assessment questions)
+
+## Evaluation Framework
+**GitHub URL:** [https://github.com/Line-Kite/CLTE](https://github.com/Line-Kite/CLTE)
+
+## Citation
+Please cite our paper if the work helps you.
+
 ```
 @inproceedings{xu2025can,
   title={Can Large Language Models Be Good Language Teachers?},