Update README.md

README.md

@@ -21,7 +21,7 @@ Released on September 27, 2024
         </p>
 </h4>
 
-# Introduction
+## Introduction
 
 MalayMMLU is the first multitask language understanding (MLU) for Malay Language. The benchmark comprises 24,213 questions spanning both primary (Year 1-6) and secondary (Form 1-5) education levels in Malaysia, encompassing 5 broad topics that further divide into 22 subjects. 
 <p align="center">
@@ -36,9 +36,9 @@ MalayMMLU is the first multitask language understanding (MLU) for Malay Language
 | **Others**     | Life Skills (Primary, Secondary), Principles of Accounting (Secondary), Economics (Secondary), Business (Secondary), Agriculture (Secondary)                                                                                                                                                                                                                                                  |
 | **Humanities** | Quran and Sunnah (Secondary), Islam (Primary, Secondary), Sports Science Knowledge (Secondary)                                                                                                                                                                                                                                                                                                 |
 
-# Result
+## Result
 
-### Zero-shot results of LLMs on MalayMMLU (First token accuracy)
+#### Zero-shot results of LLMs on MalayMMLU (First token accuracy)
 
 | **Model**               | **Language** | **Humanities** | **STEM** | **Social Science** | **Others** | **Average** |
 |-------------------------|-------------------|---------------------|---------------|-------------------------|-----------------|------------------|
@@ -63,3 +63,19 @@ MalayMMLU is the first multitask language understanding (MLU) for Malay Language
 | [Baichuan-2 (7B)](https://huggingface.co/baichuan-inc/Baichuan2-7B-Chat)         | 40.41             | 47.35               | 44.37         | 46.33                   | 43.54           | 44.30            |
 | [Komodo (7B)](https://huggingface.co/Yellow-AI-NLP/komodo-7b-base)   | 43.62             | 45.53               | 39.34         | 39.75                   | 39.48           | 41.72            |
 | [MaLLaM-v2 (5B)](https://huggingface.co/mesolitica/mallam-5b-20k-instructions-v2)| 42.56             | 46.42               | 42.16         | 40.81                   | 38.81           | 42.07            |
+
+
+
+## Citation
+
+```bibtex
+@InProceedings{MalayMMLU2024,
+    author    = {Poh, Soon Chang and Yang, Sze Jue and Tan, Jeraelyn Ming Li and  Chieng, Lawrence Leroy Tze Yao and Tan, Jia Xuan and Yu, Zhenyu and Foong, Chee Mun and Chan, Chee Seng },
+    title     = {MalayMMLU: A Multitask Benchmark for the Low-Resource Malay Language},
+    booktitle = {Empirical Methods in Natural Language Processing (EMNLP)},
+    month     = {November},
+    year      = {2024},
+}
+```
+## Feedback
+Suggestions and opinions (both positive and negative) are greatly welcome. Please contact the author by sending email to `cs.chan at um.edu.my`.