Update README.md

README.md

@@ -19,11 +19,6 @@ metrics:
 
 **XLM-RoBERTa is fine-tuned on Urdu dataset created through [CLASSER](https://huggingface.co/datasets/prachuryyaIITG/CLASSER) framework, for Fine-grained Named Entity Recognition.**
 
-This model is part of the **AWED-FiNER** collection, as presented in the paper [AWED-FiNER: Agents, Web applications, and Expert Detectors for Fine-grained Named Entity Recognition across 36 Languages for 6.6 Billion Speakers](https://huggingface.co/papers/2601.10161).
-
-- **GitHub Repository:** [AWED-FiNER](https://github.com/PrachuryyaKaushik/AWED-FiNER)
-- **Interactive Demo:** [AWED-FiNER Space](https://huggingface.co/spaces/prachuryyaIITG/AWED-FiNER)
-
 The tagset of [MultiCoNER2](https://huggingface.co/datasets/MultiCoNER/multiconer_v2) is a fine-grained tagset. The fine to coarse level mapping of the tags are as follows:
 
   * Location (LOC) : Facility, OtherLOC, HumanSettlement, Station
@@ -45,6 +40,7 @@ Learning Rate: 5e-5 <br>
 Weight Decay: 0.01 <br>
 Batch Size: 64 <br>
 
+It is part of the [AWED-PIPER](https://github.com/PrachuryyaKaushik/AWED-PIPER) ecosystem: [**Paper**](https://huggingface.co/papers/2601.10161) | [**Agent for FgNER**](https://github.com/PrachuryyaKaushik/AWED-FiNER) | [**Web App for FgNER**](https://huggingface.co/spaces/prachuryyaIITG/AWED-FiNER) | [**Agent for PII Protection**](https://github.com/PrachuryyaKaushik/AWED-PIPER) | [**Web App for PII Protection**](https://huggingface.co/spaces/prachuryyaIITG/AWED_PII_Protector)
 
 ## Citation
 
@@ -78,8 +74,8 @@ If you use this model, please cite the following papers:
       pages={31410-31418}
 }
 
-@misc{kaushik2026awedfineragentswebapplications,
-      title={AWED-FiNER: Agents, Web applications, and Expert Detectors for Fine-grained Named Entity Recognition across 36 Languages for 6.6 Billion Speakers}, 
+@misc{kaushik2026awedpiperagentswebapplications,
+      title={AWED-PIPER: Agents, Web Applications & Expert Detectors for Personally Identifiable Information Protection & Fine-grained Named Entity Recognition across 36 languages for 6.6 Billion Speakers}, 
       author={Prachuryya Kaushik and Ashish Anand},
       year={2026},
       eprint={2601.10161},