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aad32d4 5f2673b a03867b 5f2673b aad32d4 5f2673b aad32d4 5f2673b aad32d4 5f2673b aad32d4 5f2673b aad32d4 5f2673b aad32d4 5f2673b aad32d4 5f2673b aad32d4 5f2673b aad32d4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 | # PLaID++
This repository contains our flagship model's weights in our paper: [**_PLaID++: A Preference-Aligned Language Model for Targeted Inorganic Materials Design_**](https://arxiv.org/pdf/2509.07150), by [Andy Xu](https://www.linkedin.com/in/andyxuai/), [Rohan Desai](https://www.rohandesai.xyz), [Larry Wang](https://www.linkedin.com/in/larwang314/), [Gabriel Hope](https://www.linkedin.com/in/gabriel-hope-87472542/), and [Ethan Ritz](https://www.linkedin.com/in/ethan-ritz-2bba69382/).
## Summary
PLaID++ introduces an LLM fine-tuned for stable and property-targeted inorganic crystal generation. PLaID++ achieves a **~50% higher S.U.N.** (Stable, Unique, Novel) rate than prior work and robust conditional generation by space group though:
1. Leveraging a novel Wyckoff-based text encoding
2. Aligning the model using Direct Preference Optimization (DPO), an RL method guided by machine-learned interatomic potentials
3. Unified training across conditional and unconditional generation tasks

## Model
[The full PLaID++ model is available in `train_dpo/`](https://huggingface.co/HOPE-Lab-HMC/PLaID/tree/main/train_dpo).
## Citation
[Arxiv Link](https://arxiv.org/pdf/2509.07150)
```
@article{xu2025plaid++,
title={PLaID++: A Preference Aligned Language Model for Targeted Inorganic Materials Design},
author={Xu, Andy and Desai, Rohan and Wang, Larry and Hope, Gabriel and Ritz, Ethan},
journal={arXiv preprint arXiv:2509.07150},
year={2025}
}
```
## License
Most of PLaID++ is distributed under the CC BY 4.0 license. However, some components of the project are governed by different licenses: pymatgen is licensed under MIT, Hugging Face Transformers under Apache 2.0, and ASE under the GNU Lesser General Public License.
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