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English(EN) When Does Generating More Help? Disentangling Fixed-Source Synthesis from Source Expansion in Synthetic Data Scaling

新研究区分了合成数据扩展方法

作者 PulseAugur 编辑部 · [2 个来源] ·

一篇来自arXiv的新研究论文探讨了两种扩展合成数据生成的方法：源扩展（SE）和固定源合成（FSS）。该研究通过保持源材料和教师模型不变，同时改变生成预算来分离FSS。研究人员调整了一个扩展定律来适应FSS，并发现虽然SE和FSS在低预算下相当，但在高预算下，当添加更多源材料比从固定源生成更多响应更有效时，SE的表现优于FSS。研究结果表明，FSS是一个适合比较合成协议的有界扩展轴。 AI

影响 提供了一个理解和优化合成数据生成的框架，这对于训练大型AI模型至关重要。

排序理由 学术论文发布在arXiv上，详细介绍了一种新的研究方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

新研究区分了合成数据扩展方法

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学术论文发布在arXiv上，详细介绍了一种新的研究方法。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [2]

  1. arXiv cs.CL TIER_1 English(EN) · Xu Guo, Jian Tong, Zhihui Lu, Qipeng Guo ·

    生成更多何时有益？解耦固定源合成与合成数据扩展中的源扩展

    arXiv:2607.01727v1 Announce Type: new Abstract: Synthetic data can be scaled along two routes: Source Expansion (SE), which enlarges the source by adding seed materials or generators, and Fixed-Source Synthesis (FSS), which holds the source fixed and scales the generation budget.…

  2. arXiv cs.CL TIER_1 English(EN) · Qipeng Guo ·

    何时生成更多会有帮助？解耦固定源合成与合成数据扩展中的源扩展

    Synthetic data can be scaled along two routes: Source Expansion (SE), which enlarges the source by adding seed materials or generators, and Fixed-Source Synthesis (FSS), which holds the source fixed and scales the generation budget. Existing scaling studies typically expand the s…

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