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README.md
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@@ -49,6 +49,7 @@ We introduce AceCoder, the first work to propose a fully automated pipeline for
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| AceCoder-RM-32B | **72.1** | **73.7** | 70.5 | 88 | 84.5 | **78.3** | **65.5** | **76.1** |
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| Delta (AceCoder 7B - Others) | 7.5 | \-4.6 | \-6.1 | \-6.1 | \-9.1 | \-0.3 | 6.1 | 2.1 |
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| Delta (AceCoder 32B - Others) | 12.7 | 2.4 | \-0.9 | \-8 | \-4.5 | 3.6 | 9.4 | 6 |
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\* These models do not have official results as they are released later than the RM Bench paper; therefore, the authors tried our best to extend the original code base to test these models. Our implementation can be found here:
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[Modified Reward Bench / RM Bench Code](https://github.com/wyettzeng/reward-bench)
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| AceCoder-RM-32B | **72.1** | **73.7** | 70.5 | 88 | 84.5 | **78.3** | **65.5** | **76.1** |
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| Delta (AceCoder 7B - Others) | 7.5 | \-4.6 | \-6.1 | \-6.1 | \-9.1 | \-0.3 | 6.1 | 2.1 |
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| Delta (AceCoder 32B - Others) | 12.7 | 2.4 | \-0.9 | \-8 | \-4.5 | 3.6 | 9.4 | 6 |
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\* These models do not have official results as they are released later than the RM Bench paper; therefore, the authors tried our best to extend the original code base to test these models. Our implementation can be found here:
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[Modified Reward Bench / RM Bench Code](https://github.com/wyettzeng/reward-bench)
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