Add library_name and pipeline_tag

README.md

@@ -1,11 +1,13 @@
 ---
-license: apache-2.0
+base_model:
+- Qwen/Qwen2.5-32B
 datasets:
 - BytedTsinghua-SIA/DAPO-Math-17k
 language:
 - en
-base_model:
-- Qwen/Qwen2.5-32B
+license: apache-2.0
+library_name: transformers
+pipeline_tag: text-generation
 ---
 
 # FIPO: Eliciting Deep Reasoning with Future-KL Influenced Policy Optimization
@@ -70,10 +72,14 @@ The FIPO objective yields longer responses and a stronger AIME 2024 peak than th
 ## 🎈 Citation
 
 ```bibtex
-@misc{FIPO,
-  title = {FIPO: Eliciting Deep Reasoning with Future-KL Influenced Policy Optimization},
-  url = {[https://qwen-pilot.notion.site/fipo](https://qwen-pilot.notion.site/fipo)},
-  author = {Chiyu Ma and Shuo Yang and Kexin Huang and Jinda Lu and Haoming Meng and Shangshang Wang and Bolin Ding and Soroush Vosoughi and Guoyin Wang and Jingren Zhou},
-  year = {2026},
-  month = {March},
-}
+@article{ma2026fipo,
+  title={FIPO: Eliciting Deep Reasoning with Future-KL Influenced Policy Optimization},
+  author={Ma, Chiyu and Yang, Shuo and Huang, Kexin and Lu, Jinda and Meng, Haoming and Shangshang Wang and Bolin Ding and Soroush Vosoughi and Guoyin Wang and Jingren Zhou},
+  journal={arXiv preprint arXiv:2603.19835},
+  year={2026}
+}
+```
+
+## 🌻 Acknowledgement
+
+This project builds on top of the [VeRL](https://github.com/volcengine/verl) training framework and follows the practical recipe structure introduced by [DAPO](https://github.com/Bytedance-Research/DAPO).