diff --git a/beat/algorithms/loicbarrault/mt_lifelong_loop/1.py b/beat/algorithms/loicbarrault/mt_lifelong_loop/1.py
index 6a6054c..3add5dd 100644
--- a/beat/algorithms/loicbarrault/mt_lifelong_loop/1.py
+++ b/beat/algorithms/loicbarrault/mt_lifelong_loop/1.py
@@ -289,11 +289,13 @@ def get_sen_vecs(data_dict_train, src_vocab, word_embs):
 
     for index_sen, sen in enumerate(data_dict_train['src']):
         splitsen = sen.split()
+        sen_length = 0
         for token in splitsen:
             if token in src_vocab.keys():
+                sen_length += 1
                 index_token = int(src_vocab[token].split()[0])
-                sen_vecs[index_sen] = word_embs[index_token]
-        sen_vecs[index_sen] /= len(splitsen)
+                sen_vecs[index_sen] += word_embs[index_token]
+        sen_vecs[index_sen] /= sen_length
 
     return sen_vecs
 
@@ -324,11 +326,13 @@ def data_selection_emb(N, data_dict_train, train_sen_vecs, doc_input, src_vocab,
     for sen in doc_input:
         sen_vec = torch.zeros(1, word_embs.size()[1], dtype=word_embs.dtype, device=word_embs.device)
         splitsen = sen.split()
+        sen_length = 0
         for token in splitsen:
             if token in src_vocab.keys():
+                sen_length += 1
                 index = int(src_vocab[token].split()[0])
                 sen_vec += word_embs[index]
-        sen_vec /= len(splitsen)
+        sen_vec /= sen_length
         coss = cos(sen_vec, train_sen_vecs)
         coss[torch.isnan(coss)] = 0
         index_topn_sens = torch.topk(coss, n, largest=True).indices