Update README.md

README.md

@@ -125,11 +125,21 @@ On Eurovoc Dataset version 23.08 with a stratification ratio 90/10 for training/
 | NDCG@5     | 0.8625     | -               |
 | NDCG@10    | 0.8711     | -               |
 
-These values are in line with the state of the art in the field, see the publication [Large Scale Legal Text Classification Using Transformer Models](https://arxiv.org/pdf/2010.12871.pdf).
+These values are higher than the state of the art previously known in the field, see publications:
+
+- Ilias Chalkidis, Emmanouil Fergadiotis, Prodromos Malakasiotis, Nikolaos Aletras, and Ion Androutsopoulos. 2019. [Extreme Multi-Label Legal Text Classification](https://arxiv.org/abs/1905.10892): A Case Study in EU Legislation. In Proceedings of the Natural Legal Language Processing Workshop 2019, pages 78–87, Minneapolis, Minnesota. Association for Computational Linguistics.
+- I. Chalkidis, M. Fergadiotis, P. Malakasiotis and I. Androutsopoulos, "[Large-Scale Multi-Label Text Classification on EU Legislation](https://arxiv.org/abs/1906.02192)". Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019), Florence, Italy, (short papers), 2019 ()
+- Andrei-Marius Avram, Vasile Pais, and Dan Ioan Tufis. 2021. [PyEuroVoc: A Tool for Multilingual Legal Document Classification with EuroVoc Descriptors](https://arxiv.org/abs/2108.01139). In Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021), pages 92–101, Held Online. INCOMA Ltd..
+- SHAHEEN, Zein, WOHLGENANNT, Gerhard, et FILTZ, Erwin. [Large Scale Legal Text Classification Using Transformer Models](https://arxiv.org/pdf/2010.12871.pdf)
+
+
+These results make this model the de facto new reference in the domain.
+As the model is open, we encourage you to carry out your own evaluations and share them on the [discussion forum](https://huggingface.co/EuropeanParliament/eurovoc_eu/discussions)
 
 
 ## Inference Endpoint
 
+
 ### Payload example 
 
 ```json