Update README.md

Author: ZrrSkywalker

README.md

@@ -10,7 +10,7 @@ This repo proposes **LLaMA-Adapter (V2)**, a lightweight adaption method for fin
 Try out the web demo 🤗 of LLaMA-Adapter: [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/csuhan/LLaMA-Adapter)
 
 ## News
-- **[2023.04.30]** We are noticed that GPT-4 evaluation has a strong positional bias in favor of the first response. We will soon update the paper to reveal the position bias. Our approach also shows a potential to automate chatbot assessment, but still requires further research. Great thanks to [Canwen Xu](https://scholar.google.com/citations?user=oopKCDMAAAAJ&hl=en).
+- **[2023.04.30]** We are noticed that GPT-4 evaluation has a strong positional bias in favor of the first response. We will soon update the paper to reveal the position bias. GPT-4 evaluation also shows a potential to automate chatbot assessment, but still requires further research. Great thanks to [Canwen Xu](https://scholar.google.com/citations?user=oopKCDMAAAAJ&hl=en).
 - **[2023.04.30]** The technical report for **LLaMA-Adapter V2** is released at [preprint](https://arxiv.org/abs/2304.15010).
 - **[2023.04.28]** 🔥🔥 We release **LLaMA-Adapter V2 (65B)**, a multi-modal instruction model! Check out our [demos](#demos) and [code](https://github.com/ZrrSkywalker/LLaMA-Adapter/tree/main/llama_adapter_v2_chat65b)!
 - **[2023.04.15]** The **Training Code** for LLaMA-Adapter (7B) can now be found in [alpaca finetune v1](https://github.com/ZrrSkywalker/LLaMA-Adapter/tree/main/alpaca_finetuning_v1). 📌