Update README.md

README.md

@@ -48,25 +48,27 @@ Batch Size: 64 <br>
 [Prof. V Vijaya Saradhi](https://www.linkedin.com/in/vijaya-saradhi-a90a604/) <br>
 [Prof. Ashish Anand](https://www.linkedin.com/in/anandashish/)
 
-APTFiNER is a part of the [AWED-FiNER](https://github.com/PrachuryyaKaushik/AWED-FiNER) ecosystem: [**Paper**](https://huggingface.co/papers/2601.10161) | [**GitHub**](https://github.com/PrachuryyaKaushik/AWED-FiNER) | [**Interactive Demo**](https://huggingface.co/spaces/prachuryyaIITG/AWED-FiNER)
+APTFiNER is a part of the [AWED-FiNER collection](https://huggingface.co/collections/prachuryyaIITG/awed-finer). Please check: [**Paper**](https://huggingface.co/papers/2601.10161) | [**Agentic Tool**](https://github.com/PrachuryyaKaushik/AWED-FiNER) | [**Interactive Demo**](https://huggingface.co/spaces/prachuryyaIITG/AWED-FiNER)
 
 ## Sample Usage
 
-You can use the AWED-FiNER agentic tool to interact with expert models trained using this framework. Below is an example using the `smolagents` library:
-
+The AWED-FiNER agentic tool can be used to interact with expert models trained using this framework. Below is an example:
+```bash
+pip install smolagents gradio_client
+```
 ```python
-from smolagents import CodeAgent, HfApiModel
 from tool import AWEDFiNERTool
 
-# Initialize the expert tool
-ner_tool = AWEDFiNERTool()
+tool = AWEDFiNERTool(
+    space_id="prachuryyaIITG/AWED-FiNER"
+)
 
-# Initialize the agent (using a model of your choice)
-agent = CodeAgent(tools=[ner_tool], model=HfApiModel())
+result = tool.forward(
+    text="Jude Bellingham joined Real Madrid in 2023.",
+    language="English"
+)
 
-# The agent will automatically use AWED-FiNER for specialized NER
-# Case: Processing a vulnerable language (Bodo)
-agent.run("Recognize the named entities in this Bodo sentence: 'बिथाङा दिल्लियाव थाङो।'")
+print(result)
 ```
 
 ## Citation
@@ -82,6 +84,15 @@ If you use this model, please cite the following papers:
   year={2026}
 }
 
+@misc{kaushik2026awedfiner,
+  title        = {AWED-FiNER: Agents, Web Applications, and Expert Detectors for Fine-grained Named Entity Recognition across 36 Languages for 6.6 Billion Speakers},
+  author       = {Kaushik, Prachuryya and Anand, Ashish},
+  year         = {2026},
+  note         = {arXiv preprint, submitted},
+  archivePrefix= {arXiv},
+  eprint       = {submit/7163987}
+}
+
 @inproceedings{kaushik2026sampurner,
   title={SampurNER: Fine-grained Named Entity Recognition Dataset for 22 Indian Languages},
   author={Kaushik, Prachuryya and Anand, Ashish},