Update README.md

README.md

@@ -8,8 +8,7 @@ language:
 
 
 <div align="center">
-  <img src="https://github.com/Babelscape/FENICE/blob/master/new_logo.png?raw=True" height="150">
-  <img src="https://github.com/Babelscape/FENICE/blob/master/Sapienza_Babelscape.png?raw=true" height="50">
+  <img src="https://github.com/Babelscape/FENICE/blob/master/new_logo.png?raw=True" height="200", width="200">
 </div>
 
 # Factuality Evaluation of summarization based on Natural Language Inference and Claim Extraction
@@ -19,7 +18,9 @@ language:
 [![Paper](http://img.shields.io/badge/paper-ACL--anthology-B31B1B.svg)](https://aclanthology.org/2024.findings-acl.841.pdf)
 [![License: CC BY-NC-SA 4.0](https://img.shields.io/badge/License-CC%20BY--NC--SA%204.0-lightgrey.svg)](https://creativecommons.org/licenses/by-nc-sa/4.0/)
 
-
+<div align='center'>
+  <img src="https://github.com/Babelscape/FENICE/blob/master/Sapienza_Babelscape.png?raw=True" height="70">
+</div>
 FENICE (Factuality Evaluation of Summarization based on Natural Language Inference and Claim Extraction) is a factuality-oriented metric for summarization. 
 This package implements the FENICE metric, allowing users to evaluate the factual consistency of document summaries.
 
@@ -28,7 +29,7 @@ This package implements the FENICE metric, allowing users to evaluate the factua
 Factual consistency in summarization is critical for ensuring that the generated summaries accurately reflect the content of the original documents. 
 FENICE leverages NLI and claim extraction techniques to assess the factual alignment between a summary and its corresponding document.
 
-For more details, you can read the full paper: [FENICE: Factuality Evaluation of Summarization based on Natural Language Inference and Claim Extraction](https://arxiv.org/abs/2403.02270).
+For more details, you can read the full paper: [FENICE: Factuality Evaluation of Summarization based on Natural Language Inference and Claim Extraction](https://aclanthology.org/2024.findings-acl.841/).
 
 ## 🛠️ Installation
 
@@ -41,7 +42,12 @@ conda activate FENICE
 To install the FENICE package, you can use `pip`:
 
 ```sh
-pip install git+https://github.com/Babelscape/FENICE.git
+pip install FENICE
+```
+
+install spacy model:
+```sh
+python -m spacy download en_core_web_sm
 ```
 
 ## Requirements
@@ -49,7 +55,6 @@ pip install git+https://github.com/Babelscape/FENICE.git
 The package requires the following dependencies:
 
 	•	spacy==3.7.4
-	•	en_core_web_sm
 	•	fastcoref==2.1.6
 	•	transformers~=4.38.2
 	•	sentencepiece==0.2.0