Update README.md

README.md

@@ -52,8 +52,8 @@ This model represents a fundamental shift in how we approach LLM fine-tuning. In
 
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-> *"While denoising objectives exist in pre-training (e.g., BART, T5), applying **heavy stochastic token shuffling (70%)** strictly during the **Instruction Fine-Tuning (SFT)** phase for Causal LLMs to decouple logic from syntax is, to the best of our knowledge, a novel approach introduced by aifeifei798, Gemini."*
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+> "While denoising objectives exist in pre-training (e.g., BART, T5), applying **heavy stochastic token shuffling (70%)** strictly during the **Instruction Fine-Tuning (SFT)** phase for Causal LLMs to decouple logic from syntax is, to the best of our knowledge, a novel approach introduced by **aifeifei798** and **Gemini**."
+> 
 > *(虽然去噪任务在预训练中存在，但在因果语言模型的 SFT 阶段使用高强度的随机词序打乱（70%）来剥离逻辑与句法，据我们所知，这是由 aifeifei798, Gemini 首创的方法。)*
 
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