Update README.md

README.md

@@ -7,7 +7,7 @@ base_model:
 ---
 # **TL-CodeLLaMA-2**
 
-TL-CodeLLaMA-2 is a model designed for tool use, built upon CodeLLaMA-7b. It is trained on 1,217 data samples using the *TL-Training* framework and demonstrates effective performance across a variety of tool use tasks. More information can be found in the paper "[TL-Training: A Task-Feature-Based Framework for Training Large Language Models in Tool Use](https://www.arxiv.org/abs/2412.15495)".
+[EMNLP 2025] TL-CodeLLaMA-2 is a model designed for tool use, built upon CodeLLaMA-7b. It is trained on 1,217 data samples using the *TL-Training* framework and demonstrates effective performance across a variety of tool use tasks. More information can be found in the paper "[TL-Training: A Task-Feature-Based Framework for Training Large Language Models in Tool Use](https://www.arxiv.org/abs/2412.15495)".
 
 # Model Use
 
@@ -110,13 +110,33 @@ print(response)
 If you find this model useful in your research, please cite:
 
 ```bibtex
-@misc{TL-Training,
-      title={TL-Training: A Task-Feature-Based Framework for Training Large Language Models in Tool Use}, 
-      author={Junjie Ye and Yilong Wu and Sixian Li and Yuming Yang and Tao Gui and Qi Zhang and Xuanjing Huang and Peng Wang and Zhongchao Shi and Jianping Fan and Zhengyin Du},
-      year={2024},
-      eprint={2412.15495},
-      archivePrefix={arXiv},
-      primaryClass={cs.CL},
-      url={https://arxiv.org/abs/2412.15495}, 
+@inproceedings{TL-Training,
+  author       = {Junjie Ye and
+                  Yilong Wu and
+                  Sixian Li and
+                  Yuming Yang and
+                  Zhiheng Xi and
+                  Tao Gui and
+                  Qi Zhang and
+                  Xuanjing Huang and
+                  Peng Wang and
+                  Zhongchao Shi and
+                  Jianping Fan and
+                  Zhengyin Du},
+  editor       = {Christos Christodoulopoulos and
+                  Tanmoy Chakraborty and
+                  Carolyn Rose and
+                  Violet Peng},
+  title        = {TL-Training: {A} Task-Feature-Based Framework for Training Large Language
+                  Models in Tool Use},
+  booktitle    = {Findings of the Association for Computational Linguistics: {EMNLP}
+                  2025, Suzhou, China, November 4-9, 2025},
+  pages        = {239--258},
+  publisher    = {Association for Computational Linguistics},
+  year         = {2025},
+  url          = {https://aclanthology.org/2025.findings-emnlp.15/},
+  timestamp    = {Fri, 20 Feb 2026 08:07:46 +0100},
+  biburl       = {https://dblp.org/rec/conf/emnlp/YeWLYXGZHWSFD25.bib},
+  bibsource    = {dblp computer science bibliography, https://dblp.org}
 }
 ```