Update README.md

README.md

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-license: cc-by-sa-4.0
+language: fr
+license: cc-by-4.0
 ---
+
+# Cour de Cassation *titrage* prediction model (transformer-base)
+
+Model for the automatic prediction of *titrages* (keyword sequence) from *sommaires* (synthesis of legal cases). The models are described in [this paper](https://hal.inria.fr/hal-03663110/file/LREC_2022___CCass_Inria-camera-ready.pdf). If you use this model, please cite our research paper (see [below](#cite)).
+
+## Model description
+
+
+
+### Intended uses & limitations
+
+
+
+### How to use
+
+
+### Limitations and bias
+
+
+
+## Training data
+
+
+
+## Training procedure
+
+### Preprocessing
+
+
+### Training
+
+### Evaluation results
+
+Coming soon
+
+## BibTex entry and citation info
+<a name="cite"></a>
+
+If you use this work, please cite the following article:
+
+Thibault Charmet, Inès Cherichi, Matthieu Allain, Urszula Czerwinska, Amaury Fouret, Benoît Sagot and Rachel Bawden, 2022. **Complex Labelling and Similarity Prediction in Legal Texts: Automatic Analysis of France’s Court of Cassation Rulings**. In Proceedings of the 13th Language Resources and Evaluation Conference, Marseille, France.
+
+```
+@inproceedings{charmet-et-al-2022-complex,
+  tite = {Complex Labelling and Similarity Prediction in Legal Texts: Automatic Analysis of France’s Court of Cassation Rulings},
+  author = {Charmet, Thibault and Cherichi, Inès and Allain, Matthieu and Czerwinska, Urszula and Fouret, Amaury, and Sagot, Benoît and Bawden, Rachel},
+  booktitle = {Proceedings of the 13th Language Resources and Evaluation Conference},
+  year = {2022},
+  address = {Marseille, France}
+```