From b1222170eddbc3cee7c075274503b210fb2d86c9 Mon Sep 17 00:00:00 2001
From: Yigit Sever
Date: Thu, 19 Sep 2019 21:07:17 +0300
Subject: Cite Balikas et al

---
 README.md | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md
index 9b8da9c..ea0c2ba 100644
--- a/README.md
+++ b/README.md
@@ -1,6 +1,6 @@
 # Evaluating cross-lingual textual similarity on dictionary alignment
 
-This repository contains the scripts to prepare the resources for the study as well as open source implementations of the methods.
+This repository contains the scripts to prepare the resources for the study as well as open source implementations of the methods. Word Mover's Distance and Sinkhorn implementations are extended from [Cross-lingual retrieval with Wasserstein distance](https://github.com/balikasg/WassersteinRetrieval).
 
 ## Requirements
 - Python 3
@@ -56,8 +56,8 @@ Linewise aligned definition files are in `wordnets/ready`.
 
 ## Acquiring The Embeddings
 
-We use [VecMap](https://github.com/artetxem/vecmap) on [fastText](https://fasttext.cc/) embeddings.
-You can skip this step if you are providing your own polylingual embeddings.
+We use [VecMap](https://github.com/artetxem/vecmap) on [fastText](https://fasttext.cc/) embeddings. You can skip this step if you are providing your own polylingual embeddings.
+
 Otherwise;
 
 * initialize and update the VecMap submodule;
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