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Add paper link (#1)

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- Add paper link (7279bf64ed6041cf2f201ad3a5768d25732d9139)


Co-authored-by: Omar Sanseviero <osanseviero@users.noreply.huggingface.co>

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  1. README.md +1 -1
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@@ -22,7 +22,7 @@ The &lambda;-ECLIPSE model is a light weight support for multi-concept personali
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  - **Project Page:** [https://eclipse-t2i.github.io/Lambda-ECLIPSE/](https://eclipse-t2i.github.io/Lambda-ECLIPSE/)
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  - **GitHub:** [https://github.com/Maitreyapatel/lambda-eclipse-inference](https://github.com/Maitreyapatel/lambda-eclipse-inference)
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- - **Paper (arXiv):** [TBD](#)
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  Importantly, &lambda;-ECLIPSE works in pure CLIP latent space without any additional information. Hence, it's performance can be easily imporved via test-time adaption to increase the concept alignment while having solid composition alignment.
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  - **Project Page:** [https://eclipse-t2i.github.io/Lambda-ECLIPSE/](https://eclipse-t2i.github.io/Lambda-ECLIPSE/)
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  - **GitHub:** [https://github.com/Maitreyapatel/lambda-eclipse-inference](https://github.com/Maitreyapatel/lambda-eclipse-inference)
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+ - **Paper (arXiv):** [https://arxiv.org/abs/2402.05195](https://arxiv.org/abs/2402.05195)
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  Importantly, &lambda;-ECLIPSE works in pure CLIP latent space without any additional information. Hence, it's performance can be easily imporved via test-time adaption to increase the concept alignment while having solid composition alignment.
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