Update README.md

README.md

@@ -10,9 +10,9 @@ pipeline_tag: text-generation
 # Model Card
 
 ## 1. Model Details
-This model is the fine-tuned checkpoint described in the paper **"Not All Steps are Informative: On the Linearity of LLMs’ RLVR Training"**. It was trained using Reinforcement Learning (RL) to enhance reasoning capabilities.
+This model is the fine-tuned checkpoint described in the paper **"Linear Dynamics in the RLVR Training of Large Language Models"**. It was trained using Reinforcement Learning with Verifiable Rewards (RLVR) to enhance reasoning capabilities.
 
-- **Paper:** [ArXiv](https://arxiv.org/pdf/2601.04537v1)
+- **Paper:** [ArXiv](https://arxiv.org/abs/2601.04537v3)
 - **Code:** [Github](https://github.com/Miaow-Lab/RLVR-Linearity)
 - **Base Model:** [deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B)
 - **Training Method:** GRPO
@@ -36,9 +36,9 @@ For full training configurations, please refer to the `config.json` or the train
 If you use this model in your research, please cite our paper:
 
 ```bibtex
-@misc{wang2026stepsinformativelinearityllms,
-      title={Not All Steps are Informative: On the Linearity of LLMs' RLVR Training}, 
-      author={Tianle Wang and Zhongyuan Wu and Shenghao Jin and Hao Xu and Wei Chen and Ning Miao},
+@misc{wang2026lineardynamicsrlvrtraining,
+      title={Linear Dynamics in the RLVR Training of Large Language Models}, 
+      author={Tianle Wang and Jiayu Liu and Zhongyuan Wu and Shenghao Jin and Wei Chen and Hao Xu and Ning Miao},
       year={2026},
       eprint={2601.04537},
       archivePrefix={arXiv},