Update README.md

README.md

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 # KoInFoBench
 
-KoInFoBench is a specialized evaluation dataset designed to assess the performance of Large Language Models (LLMs) on capabilities of Korean instructions following.
+KoInFoBench is a specialized evaluation dataset designed to assess the performance of Large Language Models (LLMs) on capabilities of Korean instructions following.<br>
+The current version of `KoInFoBench` consists of 60 instruction sets and 233 questions.
 
 Inspired by [InFoBench](https://huggingface.co/datasets/kqsong/InFoBench) dataset, we extends their concpet by focusing on the nuances and features of Korean language.
 
  - 🖥️ Code to reproduce or evaluate own LLMs is available at [https://github.com/KIFAI/KoInFoBench](https://github.com/KIFAI/KoInFoBench)
  - 📄 Paper is under writing and open soon!
 
+### 🚀 Update
+- **2024.05.18**: add other results `gpt-4o-2024-05-13`, `claude-3-sonnet-20240229`, `solar-1-mini-chat`
+
 ## Dataset Overview
 
 ### Usage
@@ -74,17 +78,21 @@ The following is the summary of the model performance on our dataset.
 |------------------------------               |--------    |--------|-----------|
 | **claude-3-opus-20240229**                  | **0.854**  | 0.850  | 87%       |
 | **gpt-4-turbo-2024-04-09**                  | 0.850      | 0.880  | 87%       |
+| **gpt-4o-2024-05-13**                       | 0.850      | 0.863  | 89%       |
 | **gpt-4-0125-preview**                      | 0.824      | 0.824  | 83%       |
+| **claude-3-sonnet-20240229**                | 0.790      | 0.828  | 84%       |
 | **gemini-1.5-pro**                          | 0.773      | 0.811  | 83%       |
 | **meta-llama/Meta-Llama-3-70B-Instruct-**   | 0.747      | 0.863  | 84%       |
 | **hpx003**                                  | 0.691      | 0.738  | 83%       |
 | **gpt-3.5-turbo-0125**                      | 0.678      | 0.734  | 82%       |
-| **yanolja/EEVE-Korean-Instruct-10.8B-v1.0** | 0.597      | 0.730  | 79%       |
+| **solar-1-mini-chat**                       | 0.614      | 0.695  | 79%       |
+| **yanolja/EEVE-Korean-Instruct-10.8B-v1.0** | 0.597      | 0.730  | 79%       |`
 
 - `H_DRFR`: The accuracy of model responses as evaluated by the human expert
 - `A_DRFR`: The accuracy of model responses automatically evaluated by GPT-4 as employing the capability of LLM-as-a-judge
 - `Alignment`: The degree of agreement or consistency between the human and automated evaluation
 
+> Please note that the evaluation results of the LLMs presented in the above table may vary due to its randomness.
 
 ## Additional Information