LoRWeB Model

ArXiv | GitHub Repository | 🌐 Project Website | 🤗 Evaluation Dataset

Hila Manor^1,2,  Rinon Gal²,  Haggai Maron^1,2,  Tomer Michaeli¹,  Gal Chechik^2,3

¹Technion - Israel Institute of Technology    ²NVIDIA    ³Bar-Ilan University

Given a prompt and an image triplet {a, a', b} that visually describe a desired transformation, LoRWeB dynamically constructs a single LoRA from a learnable basis of LoRA modules, and produces an editing result b' that applies the same analogy to the new image.

ℹ️ Additional Information

This model is a reproduction of the original model from the paper. It was trained from scratch using Technion resources. This might introduce differences from the results reported in the paper. Please see the samples directory for examples of this model's outputs on the {a, a', b} triplets from the teaser figure.

Please see our full modelcard and further details in the GitHub Repo.

📚 Citation

If you use this model in your research, please cite:

@article{manor2026lorweb,
    title={Spanning the Visual Analogy Space with a Weight Basis of LoRAs},
    author={Manor, Hila and Gal, Rinon and Maron, Haggai and Michaeli, Tomer and Chechik, Gal},
    journal={arXiv preprint arXiv:2602.15727},
    year={2026}
}