diff --git a/README.md b/README.md
index b29b598..97c70dd 100644
--- a/README.md
+++ b/README.md
@@ -3,7 +3,7 @@
 ![CI](https://github.com/fcakyon/midv500/workflows/CI/badge.svg)
 
 ## Download and convert MIDV-500 datasets into COCO instance segmentation format
-Automatically download/unzip [MIDV-500](https://arxiv.org/abs/1807.05786) and [MIDV-2019](https://arxiv.org/abs/1910.04009) datasets and convert the annotations into COCO instance segmentation format.
+Automatically download/unzip [MIDV-500](https://doi.org/10.18287/2412-6179-2019-43-5-818-824) and [MIDV-2019](https://doi.org/10.1117/12.2558438) datasets and convert the annotations into COCO instance segmentation format.
 
 Then, dataset can be directly used in the training of Yolact, Detectron type of models.
 
@@ -14,9 +14,9 @@ MIDV-500 consists of 500 video clips for 50 different identity document types in
 
 You can find more detail on papers:
 
-[MIDV-500: A Dataset for Identity Documents Analysis and Recognition on Mobile Devices in Video Stream](https://arxiv.org/abs/1807.05786)
+[MIDV-500: A Dataset for Identity Documents Analysis and Recognition on Mobile Devices in Video Stream](https://doi.org/10.18287/2412-6179-2019-43-5-818-824)
 
-[MIDV-2019: Challenges of the modern mobile-based document OCR](https://arxiv.org/abs/1910.04009)
+[MIDV-2019: Challenges of the modern mobile-based document OCR](https://doi.org/10.1117/12.2558438)
 
 
 ## Getting started
diff --git a/midv500/__init__.py b/midv500/__init__.py
index 48badcb..74fb61a 100644
--- a/midv500/__init__.py
+++ b/midv500/__init__.py
@@ -1,6 +1,6 @@
 from __future__ import absolute_import
 
-__version__ = "0.2.0"
+__version__ = "0.2.1"
 
 from midv500.convert_dataset import convert as convert_to_coco
 
diff --git a/midv500/download_dataset.py b/midv500/download_dataset.py
index 779570b..08432f0 100644
--- a/midv500/download_dataset.py
+++ b/midv500/download_dataset.py
@@ -114,8 +114,8 @@ def download_dataset(download_dir: str, dataset_name: str = "midv500"):
     """
     This script downloads the MIDV-500 dataset with extra files and unzips the folders.
     dataset_name: str
-        "midv500": https://arxiv.org/abs/1807.05786
-        "midv2019": https://arxiv.org/abs/1910.04009
+        "midv500": https://doi.org/10.18287/2412-6179-2019-43-5-818-824
+        "midv2019": https://doi.org/10.1117/12.2558438
         "all": midv500 + midv2019
     """