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# 🌌 SpecCLIP: Aligning and Translating Spectroscopic Measurements for Stars
[](https://arxiv.org/abs/2507.01939)
[](https://github.com/Xiaosheng-Zhao/SpecCLIP)
[](https://github.com/Xiaosheng-Zhao/SpecCLIP/blob/main/LICENSE)
**SpecCLIP** is a contrastive + domain-preserving foundation model designed to align **LAMOST LRS** spectra with **Gaia XP** spectrophotometric data.
It learns a **general-purpose spectral embedding (768-dim)** that supports:
* **Stellar parameter estimation**
* **Cross-survey spectral translation** (LAMOST LRS ⟷ Gaia XP)
* **Similarity retrieval** across LAMOST LRS and GAIA XP spectra
For full documentation, installation instructions, examples, and end-to-end usage, please visit the **GitHub repository**:
👉 [https://github.com/Xiaosheng-Zhao/SpecCLIP](https://github.com/Xiaosheng-Zhao/SpecCLIP)
---
## 🔧 Available Models
The following pretrained weights are included in this model repository:
| File | Description | Embedding Dim | Param |
| -------------------------------------------- | ------------------------------------- | ------------- | ------|
| `encoders/lrs_encoder.ckpt` | LAMOST LRS masked transformer encoder | 768 | 43M |
| `encoders/xp_encoder.ckpt` | Gaia XP masked transformer encoder | 768 | 43M |
| `encoders/xp_encoder_mlp.ckpt` | Gaia XP autoencoder (MLP head) | 768 | 43M |
| `specclip/specclip_model_base.ckpt` | Gaia XP ⟷ LAMOST contrastive | 768 | 100M |
| `specclip/specclip_model_predrecon_mlp.ckpt` | CLIP alignment + pred+recon | 768 | 168M |
| `specclip/specclip_model_split_mlp.ckpt` | CLIP alignment + split pred/recon | 768 | 126M |
---
## 🧠 What the Model Does
SpecCLIP consists of:
* **Two masked transformer encoders**
– LAMOST LRS
– Gaia XP
* **Contrastive alignment loss (CLIP-style)**
* **Domain-preserving prediction & reconstruction heads**
* **Cross-modal decoder** for spectrum translation
It produces **shared embeddings** enabling multi-survey astrophysical analysis.
---
## 📄 Full Documentation
To keep the Hugging Face card concise, **all detailed instructions**, including:
* Installation
* Parameter prediction
* Spectral translation
* Retrieval
* Full examples (Python + figures)
* Acknowledgments
are available at the GitHub repo:
👉 **[https://github.com/Xiaosheng-Zhao/SpecCLIP](https://github.com/Xiaosheng-Zhao/SpecCLIP)**
---
## 📊 Citation
```bibtex
@ARTICLE{2025arXiv250701939Z,
author = {{Zhao}, Xiaosheng and {Huang}, Yang and {Xue}, Guirong and {Kong}, Xiao and
{Liu}, Jifeng and {Tang}, Xiaoyu and {Beers}, Timothy C. and
{Ting}, Yuan-Sen and {Luo}, A-Li},
title = "{SpecCLIP: Aligning and Translating Spectroscopic Measurements for Stars}",
journal = {arXiv e-prints},
keywords = {Instrumentation and Methods for Astrophysics, Solar and Stellar Astrophysics,
Artificial Intelligence, Machine Learning},
year = 2025,
month = jul,
eid = {arXiv:2507.01939},
pages = {arXiv:2507.01939},
doi = {10.48550/arXiv.2507.01939},
archivePrefix = {arXiv},
eprint = {2507.01939},
primaryClass = {astro-ph.IM},
}
```
---
## 📬 Contact
* GitHub Issues: [https://github.com/Xiaosheng-Zhao/SpecCLIP/issues](https://github.com/Xiaosheng-Zhao/SpecCLIP/issues)
* Email: [xzhao113@jh.edu](mailto:xzhao113@jh.edu)
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