Update README.md

README.md

@@ -9,6 +9,8 @@ the following methods:
 - Pre-trained Model Selection [[Code]](/examples/model_selection) [[API]](/tllib/ranking)
 - Semi-supervised Learning for Classification [[Code]](/examples/semi_supervised_learning/image_classification/) [[API]](/tllib/self_training)
 
+Besides, we maintain a collection of **_awesome papers in Transfer Learning_** in another repo [_A Roadmap for Transfer Learning_](https://github.com/thuml/A-Roadmap-for-Transfer-Learning).
+
 ### 2022.2
 We adjusted our API following our survey [Transferablity in Deep Learning](https://arxiv.org/abs/2201.05867).
 
@@ -30,7 +32,6 @@ _examples_ is still divided by learning setup.
 
 ## Introduction
 *TLlib* is an open-source and well-documented library for Transfer Learning. It is based on pure PyTorch with high performance and friendly API. Our code is pythonic, and the design is consistent with torchvision. You can easily develop new algorithms, or readily apply existing algorithms.
-Besides, we maintain a collection of awesome papers in Transfer Learning in another repo [A Roadmap for Transfer Learning](https://github.com/thuml/A-Roadmap-for-Transfer-Learning).
 
 The currently supported algorithms include: