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@@ -21,11 +21,13 @@ Welcome to IBM's series of large foundation models for sustainable materials. Ou
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  GitHub: [GitHub Link](https://github.com/IBM/materials/tree/main)
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- Paper: [arXiv:2407.20267](https://arxiv.org/abs/2407.20267)
 
 
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  # SMILES-based Transformer Encoder-Decoder (SMI-TED)
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- ![ted-smi](smi-ted.png)
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  This repository provides PyTorch source code associated with our publication, "A Large Encoder-Decoder Family of Foundation Models for Chemical Language".
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@@ -174,6 +176,19 @@ with torch.no_grad():
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  ## Citations
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  ```
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  @misc{soares2024largeencoderdecoderfamilyfoundation,
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  title={A Large Encoder-Decoder Family of Foundation Models For Chemical Language},
@@ -184,5 +199,4 @@ with torch.no_grad():
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  primaryClass={cs.LG},
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  url={https://arxiv.org/abs/2407.20267},
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  }
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-
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  ```
 
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  GitHub: [GitHub Link](https://github.com/IBM/materials/tree/main)
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+ Paper (pre-print): [arXiv:2407.20267](https://arxiv.org/abs/2407.20267)
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+
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+ Paper: [Communications Chemistry](https://rdcu.be/eujAk)
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  # SMILES-based Transformer Encoder-Decoder (SMI-TED)
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+ ![smi-ted](smi-ted.png)
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  This repository provides PyTorch source code associated with our publication, "A Large Encoder-Decoder Family of Foundation Models for Chemical Language".
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  ## Citations
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+ ```
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+ @article{soares2025open,
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+ title = {An open-source family of large encoder-decoder foundation models for chemistry},
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+ author = {Soares, Eduardo and Vital Brazil, Emilio and Shirasuna, Victor and Zubarev, Dmitry and Cerqueira, Renato and Schmidt, Kristin},
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+ journal = {Communications Chemistry},
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+ volume = {8},
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+ pages = {193},
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+ year = {2025},
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+ publisher = {Nature Portfolio},
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+ doi = {10.1038/s42004-025-01585-0},
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+ url = {https://doi.org/10.1038/s42004-025-01585-0}
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+ }
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+ ```
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  ```
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  @misc{soares2024largeencoderdecoderfamilyfoundation,
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  title={A Large Encoder-Decoder Family of Foundation Models For Chemical Language},
 
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  primaryClass={cs.LG},
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  url={https://arxiv.org/abs/2407.20267},
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  }
 
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  ```