diff --git a/README.md b/README.md
index abb3912b28b1ad4fa322c92ef5b45c61561ae127..5e55d21822c425911d4bfda66bb1a47ffd986a68 100644
--- a/README.md
+++ b/README.md
@@ -12,25 +12,25 @@ The code implementing the AiGAS-dEVL approach described above is currently being
 
 - Sample at time 1: Feature1, Feature2, ... FeatureN, TrueLabel
 - Sample at time 2: Feature1, Feature2, ... FeatureN, TrueLabel
-...
+- ...
 - Sample at time Ts: Feature1, Feature2, ... FeatureN, TrueLabel, PredictedLabel
 - Sample at time Ts+1: Feature1, Feature2, ... FeatureN, TrueLabel, PredictedLabel
 - Sample at time Ts+2: Feature1, Feature2, ... FeatureN, TrueLabel, PredictedLabel
-... 
+- ... 
 
 For more information, please contact the corresponding author (Maria Arostegi, maria.arostegi@tecnalia.com).
 
 ## Please cite this work as:
 
-@misc{arostegi2024,
-      title={{AiGAS-dEVL}: An Adaptive Incremental Neural Gas Model for Drifting Data Streams under Extreme Verification Latency}, 
-      author={Maria Arostegi and Miren Nekane Bilbao and Jesus L. Lobo and Javier Del Ser},
-      year={2024},
-      eprint={waiting for ArXiV acceptance},
-      archivePrefix={arXiv},
-      primaryClass={cs.AI},
-      url={https://arxiv.org}, 
-}
+> @misc{arostegi2024,
+>      title={{AiGAS-dEVL}: An Adaptive Incremental Neural Gas Model for Drifting Data Streams under Extreme Verification Latency}, 
+>      author={Maria Arostegi and Miren Nekane Bilbao and Jesus L. Lobo and Javier Del Ser},
+>      year={2024},
+>      eprint={waiting for ArXiV acceptance},
+>      archivePrefix={arXiv},
+>      primaryClass={cs.AI},
+>      url={https://arxiv.org}, 
+>}