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@@ -30,7 +30,7 @@ GraphGen: Enhancing Supervised Fine-Tuning for LLMs with Knowledge-Driven Synthe
 GraphGen is a framework for synthetic data generation guided by knowledge graphs. 
 
 It begins by constructing a fine-grained knowledge graph from the source text，then identifies knowledge gaps in LLMs using the expected calibration error metric, prioritizing the generation of QA pairs that target high-value, long-tail knowledge.
-Furthermore, GraphGen incorporates multi-hop neighborhood sampling to capture complex relational information and employs style-controlled generation to diversify the resulting QA data. 
+Furthermore, GraphGen incorporates multi-hop neighborhood sampling to capture complex relational information and employs style-controlled generation to diversify the resulting QA data. Here is our [paper](https://github.com/open-sciencelab/GraphGen/tree/main/resources/GraphGen.pdf).
 
 ## 🚀 Quick Start
 
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