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@@ -7,15 +7,6 @@ Our goal is to develop effective and efficient data preparation systems and algo
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  ## Newly Released Papers and Code
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  πŸ”₯ 2024/08/14 Llama3-PBM-Nova-70B Model is released! [πŸ€— Huggingface](https://huggingface.co/PKU-Baichuan-MLSystemLab/Llama3-PBM-Nova-70B)
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- | Model | Arena-Hard | MixEval-Hard | Alpaca-Eval 2.0 |
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- |------------------------|------------|--------------|-----------------|
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- | GPT-4Turbo (04/09) | 82.6% | 62.6 | 55.0% |
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- | GPT-4o (05/13) | 79.2% | 64.7 | 57.5% |
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- | Gemini 1.5 Pro | 72.0% | 58.3 | - |
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- | Llama3-PBM-Nova-70B | 74.5% | 58.1 | 61.23% |
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- | Llama-3.1-70B-Instruct | 55.7% | - | 38.1% |
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- | Llama-3-70B-Instruct | 46.6% | 55.9 | 34.4% |
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  πŸ”₯ 2024/08/07 PAS: Data-Efficient Plug-and-Play Prompt Augmentation System [🌴 Repo](https://github.com/PKU-Baichuan-MLSystemLab/PAS) [🌲 arXiv](https://arxiv.org/abs/2407.06027)
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  πŸ”₯ 2024/08/02 CFBench: A Comprehensive Constraints-Following Benchmark for LLMs [🌴 Repo](https://github.com/PKU-Baichuan-MLSystemLab/CFBench) [🌲 arXiv](https://arxiv.org/abs/2408.01122)
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  ## Newly Released Papers and Code
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  πŸ”₯ 2024/08/14 Llama3-PBM-Nova-70B Model is released! [πŸ€— Huggingface](https://huggingface.co/PKU-Baichuan-MLSystemLab/Llama3-PBM-Nova-70B)
 
 
 
 
 
 
 
 
 
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  πŸ”₯ 2024/08/07 PAS: Data-Efficient Plug-and-Play Prompt Augmentation System [🌴 Repo](https://github.com/PKU-Baichuan-MLSystemLab/PAS) [🌲 arXiv](https://arxiv.org/abs/2407.06027)
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  πŸ”₯ 2024/08/02 CFBench: A Comprehensive Constraints-Following Benchmark for LLMs [🌴 Repo](https://github.com/PKU-Baichuan-MLSystemLab/CFBench) [🌲 arXiv](https://arxiv.org/abs/2408.01122)
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