Update README

README.md

@@ -92,10 +92,10 @@ configs:
 This dataset provides a focused benchmark for retrieval and generation tasks related to ECSS (European Cooperation for Space Standardization) documents. It includes a set of documents, queries, relevance judgments (qrels), and page images.
 
 - Number of Documents: 196
-- Number of Queries: 42
+- Number of Queries: 67
 - Number of Pages: 22700
-- Number of Relevance Judgments (qrels): 58
-- Average Number of Pages per Query: 1.4
+- Number of Relevance Judgments (qrels): 89
+- Average Number of Pages per Query: 1.3
 
 ## Dataset Structure (Hugging Face Datasets)
 
@@ -121,13 +121,22 @@ from datasets import load_dataset
 dataset_queries_test = load_dataset("FOR-sight-ai/ECSS-1.0", "queries", split="test")
 ```
 
+## Results
+
+| Model Name | nDCG@10 |
+| :--- | ---: |
+| bm25 | 0.43 |
+| bge-large-en-v1.5 | 0.44 |
+| nomic-embed-multimodal-3b | 0.59 |
+| colqwen2.5-v0.2 | 0.68 |
+
 ## Citation
 
 If you use this dataset in your research or work, please cite:
 
 ```bibtex
 @misc{ecssbenchmark2025,
-  title={ECSS benchmark},
+  title={ECSS RAG benchmark},
   author={Francois Lancelot and Nawal Ould Amer and Benjamin Fourreau and Catherine Kobus and Marion-Cécile Martin},
   primaryClass={cs.IR},
   year={2025},