Add paper link and update model card metadata

README.md

@@ -1,19 +1,22 @@
 ---
-license: cc-by-nc-4.0
 language:
 - en
+library_name: transformers
+license: cc-by-nc-4.0
+pipeline_tag: text-generation
 tags:
 - medical
 - text-generation
 - language-model
 - biopan
 - jepa
-library_name: transformers
-pipeline_tag: text-generation
+arxiv: 2601.22128
 ---
 
 # SMB-v1-8B-Structure
 
+This repository contains the model weights for **SMB-v1-8B-Structure**, as introduced in the paper [The Patient is not a Moving Document: A World Model Training Paradigm for Longitudinal EHR](https://huggingface.co/papers/2601.22128).
+
 ## Documentation & Quickstart
 
 For a comprehensive guide on getting started, architecture details, and advanced usage, please visit our official documentation: [**📖 SMB-v1 Quickstart Guide**](https://docs.standardmodel.bio/get-started/quickstart)
@@ -29,7 +32,7 @@ For a comprehensive guide on getting started, architecture details, and advanced
 
 ## Model Description
 
-**SMB-v1-1.7B-Structure** is the initial release of the SMB-v1 family, specifically engineered to model the complex, time-varying dynamics of cancer biology through structured clinical signals. It treats structured clinical data as a multimodal environment, fusing heterogeneous data streams into a unified patient state representation.
+**SMB-v1-8B-Structure** is the initial release of the SMB-v1 family, specifically engineered to model the complex, time-varying dynamics of cancer biology through structured clinical signals. It treats structured clinical data as a multimodal environment, fusing heterogeneous data streams into a unified patient state representation.
 
 Unlike general-purpose models, SMB-v1 is designed to ingest and synthesize diverse structured modalities across the patient journey, including:
 
@@ -74,7 +77,7 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
 from smb_biopan_utils import process_ehr_info
 
 # 1. Load Model and Tokenizer
-model_id = "standardmodelbio/SMB-v1-1.7B-Structure"
+model_id = "standardmodelbio/SMB-v1-8B-Structure"
 tokenizer = AutoTokenizer.from_pretrained(model_id)
 model = AutoModelForCausalLM.from_pretrained(
     model_id,
@@ -114,11 +117,10 @@ print(f"Patient Representation Shape: {patient_embedding.shape}")
 If you use this model in your research or application, please cite:
 
 ```bibtex
-@misc{biopan_omni,
-  author = {standardmodelbio},
-  title = {SMB-v1-8B-Structure},
-  year = {2025},
-  publisher = {HuggingFace},
-  url = {https://huggingface.co/standardmodelbio/SMB-v1-8B-Structure}
+@article{chen2025patient,
+  title={The Patient is not a Moving Document: A World Model Training Paradigm for Longitudinal EHR},
+  author={Chen, Jiuhai and Yang, Jianwei and Wu, Haiping and Li, Dianqi and Gao, Jianfeng and Zhou, Tianyi and Xiao, Bin},
+  journal={arXiv preprint arXiv:2601.22128},
+  year={2025}
 }
 ```