Product discovery is a crucial component for online shopping. However, item-to-item recommendations today do not allow users to explore changes along selected dimensions: given a query item, can a model suggest something similar but in a different color? We consider item recommendations of the comparative nature (e.g. "something darker") and show how CLIP-based models can support this use case in a zero-shot manner. Leveraging a large model built for fashion, we introduce GradREC and its industry potential, and offer a first rounded assessment of its strength and weaknesses.
Cite
@article{arxiv.2204.02473,
title = {"Does it come in black?" CLIP-like models are zero-shot recommenders},
author = {Patrick John Chia and Jacopo Tagliabue and Federico Bianchi and Ciro Greco and Diogo Goncalves},
journal= {arXiv preprint arXiv:2204.02473},
year = {2022}
}