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After data generation, you can use [LLaMA-Factory](https://github.com/hiyouga/LLaMA-Factory) and [xtuner](https://github.com/InternLM/xtuner) to finetune your LLMs.
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## 📌 Latest Updates
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- 🎉 **2026.04.13**: The paper based on GraphGen, *Knowledge-to-Verification: Exploring RLVR for LLMs in Knowledge-Intensive Domains*, has been accepted to the **ACL 2026** Main Conference! Congratulations! [Code](https://github.com/superfarther/K2V)
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- 🎉 **2026.04.13**: The paper based on GraphGen, *Knowledge-to-Verification: Exploring RLVR for LLMs in Knowledge-Intensive Domains*, has been accepted to the **ACL 2026** Main Conference! Congratulations! [Code](https://github.com/SeedScientist/K2V)
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- **2026.02.04**: We support HuggingFace Datasets as input data source for data generation now.
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- **2026.01.15**: **LLM benchmark synthesis** now supports single/multiple-choice & fill-in-the-blank & true-or-false—ideal for education 🌟🌟
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