update readme with arxiv paper link

README.md

@@ -12,4 +12,13 @@ license: apache-2.0
 short_description: 'Demo: Unifying Scheme for Extractive Content Selection Tasks'
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+[![arXiv](https://img.shields.io/badge/arXiv-2507.16922-B31B1B.svg)](http://arxiv.org/abs/2507.16922) [![PyPI](https://img.shields.io/pypi/v/igcs.svg)](https://pypi.org/project/igcs/) [![GitHub Stars](https://img.shields.io/github/stars/shmuelamar/igcs.svg?style=social)](https://github.com/shmuelamar/igcs)
+
+## 🚀 Welcome to the IGCS Live Demo!
+
+This is a demo for the paper titled [**“A Unifying Scheme for Extractive Content Selection Tasks”**][arxiv-paper] — try Instruction‑Guided Content Selection on **any**
+text or code: use the demo text or upload your document, enter an instruction, choose a model, and hit **Submit** to see the most relevant spans highlighted!
+
+🔍 Learn more in our [paper][arxiv-paper] and explore the full [GitHub repo](https://github.com/shmuelamar/igcs) ⭐. Enjoy! 🎉
+
+[arxiv-paper]: http://arxiv.org/abs/2507.16922 "A Unifying Scheme for Extractive Content Selection Tasks"

app.py

@@ -74,6 +74,17 @@ DEFAULT_MODEL = MODELS_LIST[1][1]
 MAX_INPUT_TOKENS = 4500
 MAX_PROMPT_TOKENS = 256
 
+INTRO_TEXT = """
+## 🚀 Welcome to the IGCS Live Demo!
+
+This is a demo for the paper titled [**“A Unifying Scheme for Extractive Content Selection Tasks”**][arxiv-paper] — try Instruction‑Guided Content Selection on **any**
+text or code: use the demo text or upload your document, enter an instruction, choose a model, and hit **Submit** to see the most relevant spans highlighted!
+
+🔍 Learn more in our [paper][arxiv-paper] and explore the full [GitHub repo](https://github.com/shmuelamar/igcs) ⭐. Enjoy! 🎉
+
+[arxiv-paper]: http://arxiv.org/abs/2507.16922 "A Unifying Scheme for Extractive Content Selection Tasks"
+"""
+
 
 @spaces.GPU
 def completion(prompt: str, model_id: str):
@@ -254,9 +265,7 @@ def process_igcs_request(selection_instruction: str, model_id: str, doc_data: li
 def get_app() -> gr.Interface:
     with gr.Blocks(title="Instruction-guided content selection", theme="ocean", head="") as app:
         with gr.Row():
-            gr.Markdown(
-                "Instruction-guided content selection Demo. Check the [GitHub repo](https://github.com/shmuelamar/igcs) and our [paper]() for more info."
-            )
+            gr.Markdown(INTRO_TEXT)
         with gr.Row(equal_height=True):
             with gr.Column(scale=2, min_width=300):
                 prompt_text = gr.Dropdown(