Improve model card: add pipeline tag, paper and code links

README.md

@@ -1,22 +1,29 @@
 ---
-license: llama3
 base_model: meta-llama/Llama-3.1-8B-Instruct
+license: llama3
+pipeline_tag: text-generation
 tags:
-  - biology
-  - protein
-  - molecule
-  - dna
-  - rna
-  - multimodal
-  - structure-grounded
+- biology
+- protein
+- molecule
+- dna
+- rna
+- multimodal
+- structure-grounded
 ---
 
 # Cuttlefish
 
 **Cuttlefish** is a unified all-atom multimodal LLM that grounds language reasoning in geometric cues while scaling structural tokens with structural complexity. Built on Llama-3.1-8B-Instruct, it extends the base LLM with a graph encoder and a Scaling-Aware Patching connector for processing proteins, molecules, DNA, and RNA structures.
 
+The model was introduced in the paper [Scaling-Aware Adapter for Structure-Grounded LLM Reasoning](https://huggingface.co/papers/2602.02780).
+
+**Code**: [https://github.com/zihao-jing/Cuttlefish](https://github.com/zihao-jing/Cuttlefish)
+
 ## Quick start
 
+To use the model, you can download the weights using `huggingface_hub`. Running inference requires the original codebase.
+
 ```python
 from huggingface_hub import snapshot_download
 
@@ -55,3 +62,15 @@ The `<STRUCTURE>` placeholder in the user message is replaced by the encoded str
 | Cuttlefish-Encoder | [zihaojing/Cuttlefish-Encoder](https://huggingface.co/zihaojing/Cuttlefish-Encoder) |
 | SFT instruction data | [zihaojing/Cuttlefish-SFT-Data](https://huggingface.co/datasets/zihaojing/Cuttlefish-SFT-Data) |
 | Encoder pretraining data | [zihaojing/Cuttlefish-Encoder-Data](https://huggingface.co/datasets/zihaojing/Cuttlefish-Encoder-Data) |
+
+## Citation
+
+```bibtex
+@article{jing2026cuttlefish,
+  title     = {Cuttlefish: Scaling-Aware Adapter for Structure-Grounded LLM Reasoning},
+  author    = {Jing, Zihao and Zeng, Qiuhao and Fang, Ruiyi and Li, Yan Yi and Sun, Yan and Wang, Boyu and Hu, Pingzhao},
+  booktitle = {Proceedings of the 43rd International Conference on Machine Learning (ICML)},
+  year      = {2026},
+  url       = {https://arxiv.org/abs/2602.02780}
+}
+```