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README.md
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@@ -70,14 +70,16 @@ Decomposed Requirements Following Ratio(DRFR) is the metric to evaluate how LLMs
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This metric calculates the average accuracy across answers to the decomposed questions for each instruction.
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The following is the summary of the model performance on our dataset.
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| Model
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| **claude-3-opus-20240229**
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| **gpt-
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| **hpx003**
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- `H_DRFR`: The accuracy of model responses as evaluated by the human expert
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- `A_DRFR`: The accuracy of model responses automatically evaluated by GPT-4 as employing the capability of LLM-as-a-judge
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This metric calculates the average accuracy across answers to the decomposed questions for each instruction.
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The following is the summary of the model performance on our dataset.
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| Model | H_DRFR | A_DRFR | Alignment |
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|------------------------------ |-------- |--------|-----------|
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| **claude-3-opus-20240229** | **0.854** | 0.850 | 87% |
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| **gpt-4-turbo-2024-04-09** | 0.850 | 0.880 | 87% |
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| **gpt-4-0125-preview** | 0.824 | 0.824 | 83% |
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| **gemini-1.5-pro** | 0.773 | 0.811 | 83% |
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| **meta-llama/Meta-Llama-3-70B-Instruct-** | 0.747 | 0.863 | 84% |
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| **hpx003** | 0.691 | 0.738 | 83% |
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| **gpt-3.5-turbo-0125** | 0.678 | 0.734 | 82% |
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| **yanolja/EEVE-Korean-Instruct-10.8B-v1.0** | 0.597 | 0.730 | 79% |
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- `H_DRFR`: The accuracy of model responses as evaluated by the human expert
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- `A_DRFR`: The accuracy of model responses automatically evaluated by GPT-4 as employing the capability of LLM-as-a-judge
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