Salesforce/E1-AceReason-14B

Introduction

E1-AceReason-14B is a language model fine-tuned from AceReason-Nemotron-14B. It is trained for Elastic Reasoning by budget-constrained rollout strategy, integrated into GRPO, which teaches the model to reason adaptively when the thinking process is cut short and generalizes effectively to unseen budget constraints without additional training.

Usage

For detailed usage, please refer to repo.

Performance on AIME24 (Avg@16)

Note: We did not tune the training hyperparameters. The performance may slightly differ from the results reported in the original paper due to differences in the environment setup.

Model	Tokens	Acc (%)	Tokens	Acc (%)	Tokens	Acc (%)	Tokens	Acc (%)	Tokens	Acc (%)
AceReason-Nemotron-14B	13833	76.5	-	-	-	-	-	-	-	-
E1-AceReason-14B	8376	75.4	1318	13.3	1736	22.7	2660	33.8	3448	44.6

Performance on LiveCodeBenchv5 (Avg@8)

Note: We did not tune the training hyperparameters. The performance may slightly differ from the results reported in the original paper due to differences in the environment setup.

Model	Tokens	Acc (%)	Tokens	Acc (%)	Tokens	Acc (%)	Tokens	Acc (%)	Tokens	Acc (%)
AceReason-Nemotron-14B	16669	59.2	-	-	-	-	-	-	-	-
E1-AceReason-14B	10796	57.8	1314	31.3	1810	36.3	2743	40.2	3585	43.5

Citation

@article{xu2025scalable,
  title={Scalable Chain of Thoughts via Elastic Reasoning},
  author={Xu, Yuhui and Dong, Hanze and Wang, Lei and Sahoo, Doyen and Li, Junnan and Xiong, Caiming},
  journal={arXiv preprint arXiv:2505.05315},
  year={2025}
}

Ethical Considerations

This release is for research purposes only in support of an academic paper. Our models, datasets, and code are not specifically designed or evaluated for all downstream purposes. We strongly recommend users evaluate and address potential concerns related to accuracy, safety, and fairness before deploying this model. We encourage users to consider the common limitations of AI, comply with applicable laws, and leverage best practices when selecting use cases, particularly for high-risk scenarios where errors or misuse could significantly impact people's lives, rights, or safety. For further guidance on use cases, refer to our AUP and AI AUP.