Update README.md

README.md

@@ -15,12 +15,15 @@ papers:
 
 This repository contains a collection of neural network models trained on seven tabular datasets for the study:
 
-**Exposing the Illusion of Fairness (EIF): Auditing Vulnerabilities to Distributional Manipulation Attacks**  
+**Exposing the Illusion of Fairness (EIF): Auditing Vulnerabilities to Distributional Manipulation Attacks**  <br/>
 https://arxiv.org/abs/2507.20708  
 
-Codebase:  
+Codebase:   <br/>
 https://github.com/ValentinLafargue/Inspection  
 
+Results: <br/>
+https://huggingface.co/datasets/ValentinLAFARGUE/EIF-Manipulated-distributions
+
 Each model corresponds to a specific dataset and is designed to analyze fairness properties rather than maximize predictive performance.
 
 ## 🧠 Model Description
@@ -55,6 +58,11 @@ https://www.kaggle.com/datasets/sgpjesus/bank-account-fraud-dataset-neurips-2022
 - Other datasets: 20,000 test samples  
 - Sensitive attributes are used for fairness evaluation  
 
+### Results and manipulated results
+
+The results obtained on the tests samples, and their fairwashed counterparts are directly available on [Hugging Face](https://huggingface.co/datasets/ValentinLAFARGUE/EIF-Manipulated-distributions).
+
+
 ## 📈 Predictive Performance (Accuracy)
 
 | Dataset | Accuracy |