Update README.md

README.md

@@ -8,11 +8,11 @@ pinned: true
 ---
 # ConTEB: Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings
 
-[![arXiv](https://img.shields.io/badge/arXiv-2407.01449-b31b1b.svg?style=for-the-badge)](https://arxiv.org/abs/XXX)
+[![arXiv](https://img.shields.io/badge/arXiv-2505.24782-b31b1b.svg?style=for-the-badge)](https://arxiv.org/abs/2505.24782)
 
 <img src="https://cdn-uploads.huggingface.co/production/uploads/60f2e021adf471cbdf8bb660/jq_zYRy23bOZ9qey3VY4v.png" width="800">
 
-This organization contains all artifacts released with our preprint [*Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings*](https://arxiv.org/abs/XXX),
+This organization contains all artifacts released with our preprint [*Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings*](https://arxiv.org/abs/2505.24782),
 including the [ConTEB](https://huggingface.co/collections/illuin-conteb/conteb-datasets-6839fffd25f1d3685f3ad604) benchmark.
 
 ### Abstract
@@ -32,7 +32,7 @@ We open-source all artifacts here and at https://github.com/illuin-tech/contextu
 - [*(Code) Contextual Document Engine*](https://github.com/illuin-tech/contextual-embeddings): The code used to train and run inference with our architecture.
 - [*(Code) ConTEB Benchmarkk*](https://github.com/illuin-tech/conteb): A Python package/CLI tool to evaluate document retrieval systems on the ConTEB benchmark.
 - [*Blog*](https://huggingface.co/XXX): TODO
-- [*Preprint*](https://huggingface.co/XXX): The paper with all details !
+- [*Preprint*](https://arxiv.org/abs/2505.24782): The paper with all details !
 
 ## Contact
 
@@ -44,7 +44,14 @@ We open-source all artifacts here and at https://github.com/illuin-tech/contextu
 If you use any datasets or models from this organization in your research, please cite the original dataset as follows:
 
 ```latex
-@misc{
+@misc{conti2025contextgoldgoldpassage,
+      title={Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings}, 
+      author={Max Conti and Manuel Faysse and Gautier Viaud and Antoine Bosselut and Céline Hudelot and Pierre Colombo},
+      year={2025},
+      eprint={2505.24782},
+      archivePrefix={arXiv},
+      primaryClass={cs.IR},
+      url={https://arxiv.org/abs/2505.24782}, 
 }
 ```