diff --git a/model_zoo/official/cv/openpose/README.md b/model_zoo/official/cv/openpose/README.md
index 04e73e0e97..68798789dd 100644
--- a/model_zoo/official/cv/openpose/README.md
+++ b/model_zoo/official/cv/openpose/README.md
@@ -41,7 +41,7 @@ In the currently provided training script, the coco2017 data set is used as an e
  ````bash
      wget http://images.cocodataset.org/zips/train2017.zip
      wget http://images.cocodataset.org/zips/val2017.zip
-     wget http://images.cocodataset.org/annotations/annotations2017.zip
+     wget http://images.cocodataset.org/annotations/annotations_trainval2017.zip
 ````
 
 - Create the mask dataset.
diff --git a/model_zoo/research/recommend/autodis/README.md b/model_zoo/research/recommend/autodis/README.md
index c35e569ecc..3d25acf90b 100644
--- a/model_zoo/research/recommend/autodis/README.md
+++ b/model_zoo/research/recommend/autodis/README.md
@@ -32,7 +32,7 @@ AutoDis leverages a set of meta-embeddings for each numerical field, which are s
 
 # [Dataset](#contents)
 
-- [1] A dataset [Criteo](https://s3-eu-west-1.amazonaws.com/kaggle-display-advertising-challenge-dataset/dac.tar.gz) used in  Huifeng Guo, Ruiming Tang, Yunming Ye, Zhenguo Li, Xiuqiang He. DeepFM: A Factorization-Machine based Neural Network for CTR Prediction[J]. 2017.
+- [1] A dataset Criteo used in  Huifeng Guo, Ruiming Tang, Yunming Ye, Zhenguo Li, Xiuqiang He. DeepFM: A Factorization-Machine based Neural Network for CTR Prediction[J]. 2017.
 
 # [Environment Requirements](#contents)