MolOptAgent-{3B/7B}

MolOptAgent is the Stage-2 model of the MolAct framework, continued training from MolEditAgent using Agentic Reinforcement Learning (GRPO).

Key Features

Objective: Optimized for multi-step molecular property optimization (e.g., LogP, Solubility, QED, Bioactivity).
Zero-Tolerance for Errors: Guided by real-time tool feedback, it minimizes "Chemical Hallucinations" and ensures nearly 100% molecular validity.
Performance: Outperforms strong reasoning models like Claude-3.7 and DeepSeek-R1 in complex property-guided editing tasks.

Links

GitHub Repository: https://github.com/little1d/MolAct
ArXiv https://arxiv.org/abs/2512.20135

If you use MolAct in your research, please cite:

@article{molact2025,
  title={MolAct: An Agentic RL Framework for Molecular Editing and Property Optimization},
  author={Zhuo Yang and Yeyun Chen and Jiaqing Xie and Ben Gao and Shuaike Shen and Wanhao Liu and Liujia Yang and Beilun Wang and Tianfan Fu and Yuqiang Li},
  year={2025},
  eprint={2512.20135},
  archivePrefix={arXiv},
  primaryClass={cs.AI},
  url={https://arxiv.org/abs/2512.20135}
}