Update README: add paper link, GitHub links, and open-source resources table

README.md

@@ -36,8 +36,20 @@ sequences** spanning all domains of life.
 > - `EVA_1.4B_CLM`: an additional 1.4B checkpoint trained exclusively with the CLM objective.
 
 For instructions, details, and examples, please refer to our 
-[technical report](https://arxiv.org/abs/XXXX.XXXXX) and 
-[GitHub repository](https://github.com/kevinhyj/EVA1).
+[technical report](https://www.biorxiv.org/content/10.64898/2026.03.17.712398v1) and 
+[GitHub repository](https://github.com/GENTEL-lab/EVA).
+
+## Open-Source Resources
+
+| Resource | Link | Description |
+|----------|------|-------------|
+| 📄 Paper | [bioRxiv](https://www.biorxiv.org/content/10.64898/2026.03.17.712398v1) | Technical report |
+| 💻 GitHub | [GENTEL-lab/EVA](https://github.com/GENTEL-lab/EVA) | Full codebase |
+| 🗄️ Training Data | [OpenRNA-v1-114M](https://huggingface.co/datasets/GENTEL-Lab/OpenRNA-v1-114M) | 114M full-length RNA sequences |
+| 🏋️ Training Code | [training/](https://github.com/GENTEL-lab/EVA/tree/main/training) | Pretraining, midtraining & evaluation for MoE and dense models |
+| 🔧 Finetuning Code | [finetune/](https://github.com/GENTEL-lab/EVA/tree/main/finetune) | Finetuning pipelines |
+| 🔬 Interpretability | [notebooks/interpretability_analysis/](https://github.com/GENTEL-lab/EVA/tree/main/notebooks/interpretability_analysis) | SAE interpretability analysis |
+| 🧪 Inference & Design | [tools/](https://github.com/GENTEL-lab/EVA/tree/main/tools) | Fitness prediction, CLM/GLM design, directed evolution |
 
 ## Capabilities