Improve language tag

README.md

@@ -1,36 +1,48 @@
----
-language:
-- en
-base_model:
-- Qwen/Qwen2.5-7B
-license: apache-2.0
----
-
-# ScholarCopilot-v1 Model
-
-ScholarCopilot-v1 is the foundation model of [Scholar Copilot](https://arxiv.org/abs/2504.00824). Scholar Copilot improves the academic writing process by seamlessly integrating automatic text completion and intelligent citation suggestions into a cohesive, human-in-the-loop AI-driven pipeline. Designed to enhance productivity and creativity, it provides researchers with high-quality text generation and precise citation recommendations powered by iterative and context-aware Retrieval-Augmented Generation (RAG).
-
-The current version of Scholar Copilot leverages a state-of-the-art 7-billion-parameter language model (LLM) trained on the complete Arxiv full paper corpus. This unified model for retrieval and generation is adept at making context-sensitive decisions about when to cite, what to cite, and how to generate coherent content based on reference papers.
-
-| [**🚀Project Page**](https://tiger-ai-lab.github.io/ScholarCopilot/) | [**📖Paper**](https://arxiv.org/abs/2504.00824) | [**🔗Github**](https://github.com/TIGER-AI-Lab/ScholarCopilot/) | [**🤗Data**](https://huggingface.co/datasets/TIGER-Lab/ScholarCopilot-Data-v1) | [**🤗Demo**](https://huggingface.co/spaces/TIGER-Lab/ScholarCopilot) |
-
-
-## 🌟 Key Features
-
-- ** 📝 Next-3-Sentence Suggestions: Facilitates writing by predicting the next sentences with automatic retrieval and citation of relevant reference papers.
-- ** 📚 Citation Suggestions on Demand: Provides precise, contextually appropriate paper citations whenever needed.
-- ** ✨ Full Section Auto-Completion: Assists in brainstorming and drafting comprehensive paper content and structure.
-
-The current version of ScholarCopilot primarily focuses on the introduction and related work sections of academic papers. We will support full-paper writing in future releases.
-
-## Citation
-
-Please cite our paper with
-```
-@article{wang2024scholarcopilot,
-  title={ScholarCopilot: Training Large Language Models for Academic Writing with Accurate Citations},
-  author = {Wang, Yubo and Ma, Xueguang and Nie, Ping and Zeng, Huaye and Lyu, Zhiheng and Zhang, Yuxuan and Schneider, Benjamin and Lu, Yi and Yue, Xiang and Chen, Wenhu},
-  journal={arXiv preprint arXiv:2504.00824},
-  year={2025}
-}
+---
+language:
+- zho
+- eng
+- fra
+- spa
+- por
+- deu
+- ita
+- rus
+- jpn
+- kor
+- vie
+- tha
+- ara
+base_model:
+- Qwen/Qwen2.5-7B
+license: apache-2.0
+---
+
+# ScholarCopilot-v1 Model
+
+ScholarCopilot-v1 is the foundation model of [Scholar Copilot](https://arxiv.org/abs/2504.00824). Scholar Copilot improves the academic writing process by seamlessly integrating automatic text completion and intelligent citation suggestions into a cohesive, human-in-the-loop AI-driven pipeline. Designed to enhance productivity and creativity, it provides researchers with high-quality text generation and precise citation recommendations powered by iterative and context-aware Retrieval-Augmented Generation (RAG).
+
+The current version of Scholar Copilot leverages a state-of-the-art 7-billion-parameter language model (LLM) trained on the complete Arxiv full paper corpus. This unified model for retrieval and generation is adept at making context-sensitive decisions about when to cite, what to cite, and how to generate coherent content based on reference papers.
+
+| [**🚀Project Page**](https://tiger-ai-lab.github.io/ScholarCopilot/) | [**📖Paper**](https://arxiv.org/abs/2504.00824) | [**🔗Github**](https://github.com/TIGER-AI-Lab/ScholarCopilot/) | [**🤗Data**](https://huggingface.co/datasets/TIGER-Lab/ScholarCopilot-Data-v1) | [**🤗Demo**](https://huggingface.co/spaces/TIGER-Lab/ScholarCopilot) |
+
+
+## 🌟 Key Features
+
+- ** 📝 Next-3-Sentence Suggestions: Facilitates writing by predicting the next sentences with automatic retrieval and citation of relevant reference papers.
+- ** 📚 Citation Suggestions on Demand: Provides precise, contextually appropriate paper citations whenever needed.
+- ** ✨ Full Section Auto-Completion: Assists in brainstorming and drafting comprehensive paper content and structure.
+
+The current version of ScholarCopilot primarily focuses on the introduction and related work sections of academic papers. We will support full-paper writing in future releases.
+
+## Citation
+
+Please cite our paper with
+```
+@article{wang2024scholarcopilot,
+  title={ScholarCopilot: Training Large Language Models for Academic Writing with Accurate Citations},
+  author = {Wang, Yubo and Ma, Xueguang and Nie, Ping and Zeng, Huaye and Lyu, Zhiheng and Zhang, Yuxuan and Schneider, Benjamin and Lu, Yi and Yue, Xiang and Chen, Wenhu},
+  journal={arXiv preprint arXiv:2504.00824},
+  year={2025}
+}
 ```