| # 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. |
|
|