Update README.md

README.md

@@ -30,3 +30,96 @@ configs:
  - split: test
  path: data/test-*
 ---
+
+# 🌠 KoCommonGEN v2
+
+KoCommonGEN v2: A Benchmark for Navigating Korean Commonsense Reasoning Challenges in Large Language Models (ACL 2024-Findings)
+
+*Jaehyung Seo, Jaewook Lee, Chanjun Park, SeongTae Hong, Seungjun Lee and Heuiseok Lim*
+
+🏫 [NLP & AI Lab](https://blpkorea.cafe24.com/wp/), Korea University
+
+---
+### 🔥 News
+- September 27, 2023: Provided data support for the [Open Ko-LLM Leaderboard](https://huggingface.co/spaces/upstage/open-ko-llm-leaderboard)
+- August 7, 2024: Dataset Release
+- August 10, 2024: Experimental Results for the New Models Added
+- August 14, 2024: Presented a research paper at ACL 2024
+
+
+
+
+
+### 👥 Human Evaluation
+
+We recruited 22 native Korean speaking volunteers as human evaluators and paid them $0.8 per question.
+
+| Model | # | Average Score | cohen's kappa | Krippendorff's alpha |
+| :-------: | :--: | :-----------: | :-----------: | :------------------: |
+| **Human** | 22 | 0.8395 | 0.7693 | 0.7706 |
+
+### 🤖 Models (August 10, 2024)
+
+The results of 2-shot evaluation of the newly released models.
+
+| Model | Size | Acc_norm | Stderr | Link |
+| :----------------------------: | :---: | :--------: | :----: | :----------------------------------------------------------: |
+| **GPT-4** (June 13, 2023) | | **0.7450** | | |
+| **Mistral-Nemo-Instruct** | 12B | 0.6612 | 0.0163 | [🔗](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407) |
+| **Mistral-Nemo-Base** | 12B | 0.6340 | 0.0166 | [🔗](https://huggingface.co/mistralai/Mistral-Nemo-Base-2407) |
+| **Meta-Llama-3.1-8B** | 8B | 0.6246 | 0.0166 | [🔗](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B) |
+| **QWEN2-7B base** | 7B | 0.6187 | 0.0167 | [🔗](https://huggingface.co/Qwen/Qwen2-7B) |
+| **EXAONE-3.0-7.8B-Instruct** | 7.8B | 0.6088 | 0.0168 | [🔗](https://huggingface.co/LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct) |
+| **MLP-KTLim-Bllossom-8B** | 8B | 0.6057 | 0.0168 | [🔗](https://huggingface.co/MLP-KTLim/llama-3-Korean-Bllossom-8B) |
+| **Meta-Llama-3.1-8B-Instruct** | 8B | 0.6057 | 0.0168 | [🔗](meta-llama/Meta-Llama-3.1-8B-Instruct) |
+| **KULLM3** | 10.8B | 0.6033 | 0.0168 | [🔗](https://huggingface.co/nlpai-lab/KULLM3) |
+| **QWEN2-7B inst** | 7B | 0.5832 | 0.017 | [🔗](Qwen/Qwen2-7B-Instruct) |
+| **Gemma-2-9b-it** | 9B | 0.5714 | 0.0170 | [🔗](https://huggingface.co/google/gemma-2-9b-it) |
+| **Aya-23-8B** | 8B | 0.5159 | 0.0172 | [🔗](CohereForAI/aya-23-8B) |
+| **Allganize-Alpha-Instruct** | 8B | 0.4970 | 0.0172 | [🔗](https://huggingface.co/allganize/Llama-3-Alpha-Ko-8B-Instruct) |
+
+As mentioned in the paper, it is possible to evaluate various models.
+
+
+
+### 🇰🇷🇺🇸🇯🇵🇨🇳🇪🇸 Code-switching
+
+The dataset can be found on Hugging Face at: [nlpai-lab/ko_commongen_v2_code_switching](https://huggingface.co/datasets/nlpai-lab/ko_commongen_v2_code_switching)
+
+This dataset contains code-switching data for the following languages:
+- Korean (korean)
+- English (english)
+- Japanese (japan)
+- Chinese (china)
+- Spanish (espanol)
+
+(The code-switching data relies on machine translation, which may result in some inaccuracies.)
+
+### 📖 Citation
+
+```
+@inproceedings{seo2024Kocommongenv2,
+ title = "KoCommonGEN v2: A Benchmark for Navigating Korean Commonsense Reasoning Challenges in Large Language Models",
+ author = "Jaehyung Seo and Jaewook Lee and Chanjun Park and SeongTae Hong and Seungjun Lee and Heuiseok Lim",
+ booktitle = "Findings of the Association for Computational Linguistics: ACL 2024",
+ month = August,
+ year = "2024",
+ address = "Bangkok, Thailand",
+ publisher = "Association for Computational Linguistics",
+ url = "TBD",
+ doi = "TBD",
+ pages = "TBD"}
+```
+
+### 🚨 Warning!
+
+This dataset contains some instances of toxic speech.
+
+
+### 🙏 Acknowledgement
+
+We sincerely appreciate the dedication of Chanjun Park, Sanghoon Kim and Sunghun Kim (Sung Kim) from **Upstage AI** in managing one of the benchmark datasets for the
+[Open Ko-LLM LeaderBoard](https://huggingface.co/spaces/upstage/open-ko-llm-leaderboard).
+
+
+