Update README.md

README.md

@@ -1,36 +1,35 @@
 # GALAX: Graph-Augmented Language Model for Explainable Reinforcement-Guided Subgraph Reasoning in Precision Medicine
 
 <div align="center">
-  <img src="https://github.com/deepseek-ai/DeepSeek-V2/blob/main/figures/logo.svg?raw=true" width="60%" alt="DeepSeek-V3" />
+  <img src="./GALAX-logo.png" width="40%" alt="GALAX" />
 </div>
-<hr>
+
 <div align="center" style="line-height: 1;">
-  <a href="https://www.deepseek.com/" target="_blank" style="margin: 2px;">
-    <img alt="Homepage" src="https://github.com/deepseek-ai/DeepSeek-V2/blob/main/figures/badge.svg?raw=true" style="display: inline-block; vertical-align: middle;"/>
+  <!-- GitHub -->
+  <a href="https://github.com/FuhaiLiAiLab/GALAX" target="_blank" style="margin: 2px;">
+    <img alt="GitHub" src="https://img.shields.io/badge/GitHub-GALAX%20Code-181717?logo=github&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
   </a>
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+
+  <!-- Hugging Face Model -->
+  <a href="https://huggingface.co/FuhaiLiAiLab/GALAX" target="_blank" style="margin: 2px;">
+    <img alt="Hugging Face Model" src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-GALAX%20Model-ffc107?color=ffc107&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
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+
+  <!-- Hugging Face Dataset -->
+  <a href="https://huggingface.co/datasets/FuhaiLiAiLab/Target-QA" target="_blank" style="margin: 2px;">
+    <img alt="Hugging Face Dataset" src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Target--QA%20Dataset-ff6f61?color=ffc107&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
   </a>
 </div>
 
 <div align="center" style="line-height: 1;">
-  <a href="https://discord.gg/Tc7c45Zzu5" target="_blank" style="margin: 2px;">
-    <img alt="Discord" src="https://img.shields.io/badge/Discord-DeepSeek%20AI-7289da?logo=discord&logoColor=white&color=7289da" style="display: inline-block; vertical-align: middle;"/>
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+  <!-- arXiv -->
+  <a href="https://arxiv.org/abs/2509.20935" target="_blank" style="margin: 2px;">
+    <img alt="arXiv" src="https://img.shields.io/badge/arXiv-2509.20935-b31b1b?logo=arxiv&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
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-</div>
 
-<div align="center" style="line-height: 1;">
+  <!-- License -->
   <a href="LICENSE" style="margin: 2px;">
-    <img alt="License" src="https://img.shields.io/badge/License-MIT-f5de53?&color=f5de53" style="display: inline-block; vertical-align: middle;"/>
+    <img alt="License" src="https://img.shields.io/badge/License-MIT-0a4d92?logo=open-source-initiative&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
   </a>
 </div>
 
@@ -41,7 +40,7 @@
 ![GALAX Overall Architecture](./Figure3.png)
 
 **GALAX** is a graph-augmented language model that integrates:  
-- **LLaMA3-8B-Instruct** as the language backbone (QA-tuned).  
+- **LLaMA3-8B-Instruct** as the language backbone (Target-QA tuned).  
 - **Graph Attention Network (GAT)** trained on BioMedGraphica (multi-omics + knowledge graph).  
 - **Reinforcement-guided subgraph generator** for interpretable target prioritization.  
 
@@ -65,16 +64,11 @@ lm_model = AutoModelForCausalLM.from_pretrained(
     torch_dtype="auto"
 )
 
-# 2. Access graph foundation + best combined model
+# 2. Access graph foundation model
 repo_path = snapshot_download(model_id)
-
-graph_path = os.path.join(repo_path, "graph_foundation")
-print("Graph foundation files:", os.listdir(graph_path))
-
 combined_model_path = os.path.join(repo_path, "best_combined_model.pt")
-if os.path.exists(combined_model_path):
-    best_combined_model = torch.load(combined_model_path, map_location="cpu")
-    print("Loaded best_combined_model.pt successfully")
+device = "cuda" if torch.cuda.is_available() else "cpu"
+best_combined_model = torch.load(combined_model_path, map_location=device)
 ```
 
 ---
@@ -90,17 +84,6 @@ if os.path.exists(combined_model_path):
 
 ---
 
-## 📉 Baselines & Ablations
-
-- **M2T (Multiomic2Target):** Only omics → poor performance.  
-- **L3+Omics:** No QA finetuning → weak results.  
-- **L3-FT(QA)+Omics:** Large gain from QA finetuning.  
-- **GAT / G-Retriever+pre-GAT:** Partial improvements, unstable.  
-- **+ Static KG:** Minimal or negative gains.  
-- **GALAX (QA + KG + RL):** Consistent cross-dataset gains (2–5% absolute).  
-
----
-
 
 ## 📊 Results
 
@@ -146,8 +129,8 @@ GALAX consistently outperforms baselines and ablation variants.
 ## 🔬 Intended Uses
 
 - **Research use only**  
-- Target prioritization in **cancer biology**  
-- Benchmarking **graph-language foundation models** in target priorization 
+- Benchmarking **graph-language foundation models** in target priorization
+- Target prioritization in **cancer biology**
 
 ---
 
@@ -157,8 +140,10 @@ If you use this model, please cite:
 
 ```bibtex
 @article{zhang2025galax,
-  title={GALAX: Graph-Augmented Language Model for Explainable Reinforcement-Guided Subgraph Reasoning in Precision Medicine},
-  author={Zhang, Heming and Li, Fuhai and Chen, Yixin and others},
-  year={2025},
-  journal={Preprint}
-}
+  title     = {GALAX: Graph-Augmented Language Model for Explainable Reinforcement-Guided Subgraph Reasoning in Precision Medicine},
+  author    = {Zhang, Heming and Huang, Di and Li, Wenyu and Province, Michael and Chen, Yixin and Payne, Philip and Li, Fuhai},
+  journal   = {arXiv preprint arXiv:2509.20935},
+  year      = {2025},
+  doi       = {10.48550/arXiv.2509.20935},
+  url       = {https://arxiv.org/abs/2509.20935}
+}