Add pipeline tag and improve model card

README.md

@@ -1,15 +1,21 @@
+---
+pipeline_tag: text-generation
+---
+
 <h1 align="center">
   TD3B: Transition-Directed Discrete Diffusion for Allosteric Binder Generation
 </h1>
 
-<div align="center">
+<div align="center Murphy">
+ <a href="https://huggingface.co/papers/2605.09810"><img src="https://img.shields.io/badge/Paper-2605.09810-red?style=for-the-badge" alt="Paper"/></a>
  <a href="https://arxiv.org/abs/2605.09810"><img src="https://img.shields.io/badge/Arxiv-2605.09810-red?style=for-the-badge&logo=Arxiv" alt="arXiv"/></a>
-
 </div>
 
 ![Screenshot 2026-05-10 at 6.52.29 PM](https://cdn-uploads.huggingface.co/production/uploads/64cd5b3f0494187a9e8b7c69/38-6PQ83pPraF7KAs3g3E.png)
 
-TD3B is a sequence-based generative framework that designs peptide binders with specified agonist or antagonist behavior. It combines a Direction Oracle, a soft binding-affinity gate, and amortized fine-tuning of a pre-trained discrete diffusion model (MDLM).
+TD3B is a sequence-based generative framework that designs peptide binders with specified agonist or antagonist behavior. It combines a target-aware Direction Oracle, a soft binding-affinity gate, and amortized fine-tuning of a pre-trained discrete diffusion model (MDLM).
+
+The model was presented in [TD3B: Transition-Directed Discrete Diffusion for Allosteric Binder Generation](https://huggingface.co/papers/2605.09810).
 
 ## Installation
 
@@ -133,9 +139,9 @@ bash run.sh --baseline tds --device cuda:0
 @inproceedings{
   cao2026td3b,
   title={TD3B: Transition-Directed Discrete Diffusion for Allosteric Binder Generation},
-  author={Anonymous},
+  author={Hanqun Cao and Aastha Pal and Sophia Tang and Yinuo Zhang and Jingjie Zhang and Pheng Ann Heng and Pranam Chatterjee},
   booktitle={Forty-third International Conference on Machine Learning},
   year={2026},
-  url={https://openreview.net/forum?id=RNuC8Nj6rD}
+  url={https://huggingface.co/papers/2605.09810}
 }
-```
+```